The document describes a new rendering method called bidirectional ray tracing using adaptive radiosity textures. It separates surface interaction into diffuse and specular components. It computes the specular component on the fly during ray tracing, and stores the diffuse component (radiosity) in adaptive radiosity textures on diffuse surfaces. These textures adaptively subdivide to resolve sharp shadows. It uses a three-pass algorithm: 1) a size pass records visibility, 2) a light pass traces light rays to deposit photons and construct textures, 3) an eye pass traces eye rays to render the image using the textures. This hybrid approach aims to provide accurate global illumination simulation for realistic image synthesis.
The document describes implementing Phong shading over polygonal surfaces using OpenGL. Key aspects include reading mesh files to obtain vertex and face data, calculating vertex normals, setting up a light source, and applying the Phong illumination model at each point. Phong shading is computationally expensive but produces higher quality results than Gouraud shading by interpolating normals. The implementation subdivides triangles recursively until the pixel level to apply Phong's equations. Results using pyramid and octahedron meshes demonstrated Phong shading generated superior images compared to Gouraud shading.
An illumination model, also called a lighting model and sometimes referred to as a shading model, is used to calculate the intensity of light that we should see at a given point on the surface of an object.
Surface rendering means a procedure for applying a lighting model to obtain pixel intensities for all the projected surface positions in a scene.
A surface-rendering algorithm uses the intensity calculations from an illumination model to determine the light intensity for all projected pixel positions for the various surfaces in a scene.
Surface rendering can be performed by applying the illumination model to every visible surface point.
Moving Cast Shadow Detection Using Physics-based Features (CVPR 2009)Jia-Bin Huang
This document summarizes a research paper about detecting moving cast shadows in videos. It presents an approach that uses physics-based color features and Gaussian mixture models (GMMs) to model shadows. First, it derives normalized spectral ratios as global color features under assumptions of constant ambient lighting and common spectral power distributions of direct light sources. A single GMM then models these global features to characterize shadows. Additionally, pixel-based GMMs describe local gradient intensity distortions to further differentiate shadows similar to backgrounds. The pixel GMMs are updated through confidence-rated learning to accelerate convergence without needing many foreground activities.
This document describes a method for exponential contrast restoration of images captured during fog conditions to improve visibility for driving assistance systems. It begins with an introduction to how fog degrades image quality and decreases visibility distance. It then describes Koschmieder's law which models luminance attenuation through fog. The proposed method estimates the atmospheric veil through exponential modeling and uses it to restore contrast. Results show the restored images have higher clarity and more visible edges than other methods. The technique allows real-time enhancement of color and grayscale images captured in homogeneous or heterogeneous fog.
The document discusses illumination models in computer graphics. It covers direct illumination from light sources and scattering at surfaces. It also discusses global illumination techniques like shadows, reflections and refractions using ray tracing. Common lighting models include point lights, directional lights and spot lights for light sources, and Lambertian and Phong reflection models for surfaces. Global illumination methods recursively trace rays to account for effects of indirect lighting. Key terms discussed include radiant power, radiant intensity, radiance, irradiance and radiosity.
This document summarizes illumination models used in computer graphics. It describes the local illumination or Phong model which focuses on direct light impact. It works by modeling diffuse and specular reflection. The document also covers the global illumination or ray tracing model which simulates indirect light through reflection and refraction. Ray tracing is more accurate but computationally expensive. Applications discussed include environment mapping, soft shadows, blurry reflection, and motion blur. The document notes disadvantages of both models like performance issues for Phong shading and aliasing for ray tracing.
The document describes implementing Phong shading over polygonal surfaces using OpenGL. Key aspects include reading mesh files to obtain vertex and face data, calculating vertex normals, setting up a light source, and applying the Phong illumination model at each point. Phong shading is computationally expensive but produces higher quality results than Gouraud shading by interpolating normals. The implementation subdivides triangles recursively until the pixel level to apply Phong's equations. Results using pyramid and octahedron meshes demonstrated Phong shading generated superior images compared to Gouraud shading.
An illumination model, also called a lighting model and sometimes referred to as a shading model, is used to calculate the intensity of light that we should see at a given point on the surface of an object.
Surface rendering means a procedure for applying a lighting model to obtain pixel intensities for all the projected surface positions in a scene.
A surface-rendering algorithm uses the intensity calculations from an illumination model to determine the light intensity for all projected pixel positions for the various surfaces in a scene.
Surface rendering can be performed by applying the illumination model to every visible surface point.
Moving Cast Shadow Detection Using Physics-based Features (CVPR 2009)Jia-Bin Huang
This document summarizes a research paper about detecting moving cast shadows in videos. It presents an approach that uses physics-based color features and Gaussian mixture models (GMMs) to model shadows. First, it derives normalized spectral ratios as global color features under assumptions of constant ambient lighting and common spectral power distributions of direct light sources. A single GMM then models these global features to characterize shadows. Additionally, pixel-based GMMs describe local gradient intensity distortions to further differentiate shadows similar to backgrounds. The pixel GMMs are updated through confidence-rated learning to accelerate convergence without needing many foreground activities.
This document describes a method for exponential contrast restoration of images captured during fog conditions to improve visibility for driving assistance systems. It begins with an introduction to how fog degrades image quality and decreases visibility distance. It then describes Koschmieder's law which models luminance attenuation through fog. The proposed method estimates the atmospheric veil through exponential modeling and uses it to restore contrast. Results show the restored images have higher clarity and more visible edges than other methods. The technique allows real-time enhancement of color and grayscale images captured in homogeneous or heterogeneous fog.
The document discusses illumination models in computer graphics. It covers direct illumination from light sources and scattering at surfaces. It also discusses global illumination techniques like shadows, reflections and refractions using ray tracing. Common lighting models include point lights, directional lights and spot lights for light sources, and Lambertian and Phong reflection models for surfaces. Global illumination methods recursively trace rays to account for effects of indirect lighting. Key terms discussed include radiant power, radiant intensity, radiance, irradiance and radiosity.
This document summarizes illumination models used in computer graphics. It describes the local illumination or Phong model which focuses on direct light impact. It works by modeling diffuse and specular reflection. The document also covers the global illumination or ray tracing model which simulates indirect light through reflection and refraction. Ray tracing is more accurate but computationally expensive. Applications discussed include environment mapping, soft shadows, blurry reflection, and motion blur. The document notes disadvantages of both models like performance issues for Phong shading and aliasing for ray tracing.
Registration is a process that transforms multiple sets of data into a common coordinate system, allowing comparison and integration of data obtained from different measurements or viewpoints. It is used in applications like computer vision, medical imaging, and satellite imagery analysis. The registration process is necessary to align data collected under different conditions into a unified view.
A Physical Approach to Moving Cast Shadow Detection (ICASSP 2009)Jia-Bin Huang
This document presents a physics-based approach for detecting moving cast shadows in video sequences. It develops a new physical model to characterize the variation in background appearance caused by cast shadows, without making assumptions about the spectral power distributions of light sources and ambient illumination. It uses a Gaussian mixture model to learn and update the shadow model parameters over time in an unsupervised manner. Experimental results on three challenging sequences demonstrate the effectiveness of the proposed method.
The document discusses various illumination models used in computer graphics including ambient light, point light sources, distributed light sources, Beer Lambert's law, chromaticity diagrams, flat shading, Gouraud shading, the Phong illumination model, and the Ward illumination model. It provides details on how each model calculates light intensity and color values for surfaces and polygons in a 3D scene.
Ray tracing is a technique for generating images by tracing the path of light through pixels and simulating interactions with virtual objects. It can produce highly realistic images but is computationally expensive. Ray tracing works by firing rays from the eye position through each pixel into the scene, determining the nearest intersected surface, then recursively firing reflection and refraction rays to calculate each surface's contribution to pixel color. Ray intersections are organized into a tree structure to track color contributions to each pixel. At each intersection, illumination models calculate surface color based on factors like normal, light direction, and whether shadow rays to lights are blocked.
This document discusses various lighting and shading techniques used in computer graphics, including:
- Ray tracing and radiosity methods that aim to approximate physical light behavior more accurately but with higher computational cost.
- Phong illumination model that provides relatively fast approximations of light interactions.
- Calculation of diffuse and specular reflection components in the Phong model based on surface normals, light direction, and view direction.
- Different shading techniques like flat, Gouraud, and Phong shading that determine color values at polygon vertices and faces.
This document discusses different methods for shading 3D graphics objects rendered as polygons, including flat shading (assigning a single color to each polygon), Gouraud shading (interpolating colors across polygon surfaces), Phong shading (interpolating normal vectors and applying lighting models at each surface point), and fast Phong shading (approximating Phong shading calculations for improved performance). Gouraud shading improves on flat shading by removing intensity discontinuities, while Phong shading produces more realistic highlights but requires more computation.
Computer Vision: Shape from Specularities and MotionDamian T. Gordon
The document discusses using specularities and motion to extract surface shape from images. Specifically, it discusses using:
1) Structured highlights from a spherical array of light sources to determine surface orientation of specular surfaces from the detected highlights.
2) Photometric stereo with multiple light source positions to determine surface orientation of both diffuse and specular surfaces.
3) Stereo techniques using highlights detected from multiple camera views to reconstruct the 3D shape of specular surfaces.
Ray tracing is a technique for rendering 3D graphics by simulating the path of light in a scene. It works by casting rays from the viewpoint into the scene and recursively tracing the interactions of the rays with surfaces to determine what is visible. This allows for realistic lighting effects like reflections, refractions, and shadows. The core algorithm works by casting rays for each pixel to calculate the color based on ray intersections with objects, shadows, and simulating effects like reflection and refraction through recursive ray tracing.
Feature based ghost removal in high dynamic range imagingijcga
This paper presents a technique to reduce the ghost artifacts
in a high dynamic range (HDR) image. In HDR
imaging, we need to detect the motion between multiple exp
osure images of the same scene in order to
prevent the ghost artifacts
. First, w
e
establish
correspondences between the aligned reference image and the
other exposure images using the zero
-
mean normalized cross correlation (ZNCC
).
T
hen
, we
find object
moti
on regions
using
adaptive local thresholding of ZNCC feature maps and motion map clustering. In this
process, we focus on finding accurate motion regions and on reducing false detection in order to minimize
the side effects as well.
Through
experiments wit
h several sets of
low dynamic range
images captured with
different exposures, we show that the proposed method can remove the ghost artifacts better than existing
methods
.
Deferred Pixel Shading on the PLAYSTATION®3Slide_N
This document summarizes a deferred pixel shading algorithm implemented on the PlayStation 3 system. The algorithm runs pixel shaders on the Synergistic Processing Elements of the Cell processor concurrently with the GPU for rendering images. Experimental results found that running the pixel shading on 5 SPEs achieved a performance of up to 85Hz at 720p resolution, comparable to running on a high-end GPU. This indicates that the Cell processor can effectively enhance GPU performance by offloading pixel shading work.
The document describes the Phong shading model for modeling specular reflections. It explains that specular reflection results from total or near-total reflection of incident light in a concentrated region around the specular reflection angle. The Phong model sets the intensity of specular reflection proportional to the cosine of the viewing angle raised to a power 'n'. Higher values of 'n' produce shinier surfaces, while lower values produce duller surfaces. The model calculates specular reflection based on vectors representing the light source, viewer, and specular reflection direction.
Interferogram Filtering Using Gaussians Scale Mixtures in Steerable Wavelet D...CSCJournals
An interferogram filtering is presented in this paper. The main concern of the proposed scheme is to lower the residues count mean while preserving the location and jump height of the lines of phase discontinuity. The proposed method is based on a statistical model of the coefficients of multi-scale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian vector and a hidden positive scalar multiplier. Under this model, the Bayesian least squares estimate of each coefficient reduces to a weighted average of the local linear estimates over all possible values of the hidden multiplier variable. The performance of this method substantially has the advantages of reducing number of residuals without affecting line of height discontinuity.
Band Clustering for the Lossless Compression of AVIRIS Hyperspectral ImagesIDES Editor
Hyperspectral images can be efficiently compressed
through a linear predictive model, as for example the one
used in the SLSQ algorithm. In this paper we exploit this
predictive model on the AVIRIS images by individuating,
through an off-line approach, a common subset of bands, which
are not spectrally related with any other bands. These bands
are not useful as prediction reference for the SLSQ 3-D
predictive model and we need to encode them via other
prediction strategies which consider only spatial correlation.
We have obtained this subset by clustering the AVIRIS bands
via the clustering by compression approach. The main result
of this paper is the list of the bands, not related with the
others, for AVIRIS images. The clustering trees obtained for
AVIRIS and the relationship among bands they depict is also
an interesting starting point for future research.
Variable length signature for near-duplicatejpstudcorner
To get this project in ONLINE or through TRAINING Sessions,
Contact:JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83. Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry -9. Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690 , Email: jpinfotechprojects@gmail.com, web: www.jpinfotech.org Blog: www.jpinfotech.blogspot.com
Optic Flow Estimation by Deep Learning outlines several key concepts in optical flow estimation including:
- Optical flow is the apparent motion of brightness patterns in images. Estimating optical flow involves making assumptions like brightness constancy and spatial coherence.
- Classical algorithms like Lucas-Kanade and Horn-Schunck use techniques like regularization, coarse-to-fine processing, and descriptor matching to address challenges like the aperture problem, large displacements, and occlusions.
- Recent deep learning approaches like FlowNet, DeepFlow, and EpicFlow use convolutional neural networks to directly learn optical flow, achieving state-of-the-art performance on benchmarks. These approaches combine descriptor matching, variational optimization,
illumination model in Computer Graphics by irru pychukarsyedArr
The document discusses illumination models used to calculate light intensity on object surfaces in 3D scenes. It describes how surface rendering uses illumination models to determine pixel intensities. Diffuse and specular reflection are explained along with parameters like ambient light, material properties, number of light sources, attenuation, and shadows. Color considerations and transparent surfaces are also covered at a high level.
Neural Scene Representation & Rendering: Introduction to Novel View SynthesisVincent Sitzmann
The document discusses recent advances in novel view synthesis using neural rendering. It describes different approaches for representing 3D scenes like voxel grids, multi-plane images, and implicit functions. Voxel-based methods can render high quality novel views but are memory intensive. Implicit functions enable more compact representations but rendering is slow. Hybrid implicit/explicit and image-based methods provide faster rendering but cannot represent scenes globally. The document outlines open challenges in reducing rendering costs, improving generalization, and enabling new applications in scene understanding.
This paper presents a trifocal Rotman Lens Design
approach. The effects of focal ratio and element spacing on
the performance of Rotman Lens are described. A three beam
prototype feeding 4 element antenna array working in L-band
has been simulated using RLD v1.7 software. Simulated
results show that the simulated lens has a return loss of –
12.4dB at 1.8GHz. Beam to array port phase error variation
with change in the focal ratio and element spacing has also
been investigated.
Este documento presenta una introducción a la simulación de sistemas informáticos. Explica conceptos clave como entidades, eventos, actividades, estados y modelos de simulación. También describe los componentes utilizados en la simulación de sistemas informáticos como servidores, trabajos, estaciones de retardo y sumideros. Finalmente, resume los pasos para realizar un estudio de simulación incluyendo la formulación del problema, objetivos, conceptualización del modelo y colección de datos.
Introduccion a simulacion de sistemas, conceptos, clasificacion de sistemas, clasificacion de modelos, ventajas y desventajas de la simulacion, aplicaciones empresariales simulacion de sistemas, elvis del aguila, elvisdelaguila
Registration is a process that transforms multiple sets of data into a common coordinate system, allowing comparison and integration of data obtained from different measurements or viewpoints. It is used in applications like computer vision, medical imaging, and satellite imagery analysis. The registration process is necessary to align data collected under different conditions into a unified view.
A Physical Approach to Moving Cast Shadow Detection (ICASSP 2009)Jia-Bin Huang
This document presents a physics-based approach for detecting moving cast shadows in video sequences. It develops a new physical model to characterize the variation in background appearance caused by cast shadows, without making assumptions about the spectral power distributions of light sources and ambient illumination. It uses a Gaussian mixture model to learn and update the shadow model parameters over time in an unsupervised manner. Experimental results on three challenging sequences demonstrate the effectiveness of the proposed method.
The document discusses various illumination models used in computer graphics including ambient light, point light sources, distributed light sources, Beer Lambert's law, chromaticity diagrams, flat shading, Gouraud shading, the Phong illumination model, and the Ward illumination model. It provides details on how each model calculates light intensity and color values for surfaces and polygons in a 3D scene.
Ray tracing is a technique for generating images by tracing the path of light through pixels and simulating interactions with virtual objects. It can produce highly realistic images but is computationally expensive. Ray tracing works by firing rays from the eye position through each pixel into the scene, determining the nearest intersected surface, then recursively firing reflection and refraction rays to calculate each surface's contribution to pixel color. Ray intersections are organized into a tree structure to track color contributions to each pixel. At each intersection, illumination models calculate surface color based on factors like normal, light direction, and whether shadow rays to lights are blocked.
This document discusses various lighting and shading techniques used in computer graphics, including:
- Ray tracing and radiosity methods that aim to approximate physical light behavior more accurately but with higher computational cost.
- Phong illumination model that provides relatively fast approximations of light interactions.
- Calculation of diffuse and specular reflection components in the Phong model based on surface normals, light direction, and view direction.
- Different shading techniques like flat, Gouraud, and Phong shading that determine color values at polygon vertices and faces.
This document discusses different methods for shading 3D graphics objects rendered as polygons, including flat shading (assigning a single color to each polygon), Gouraud shading (interpolating colors across polygon surfaces), Phong shading (interpolating normal vectors and applying lighting models at each surface point), and fast Phong shading (approximating Phong shading calculations for improved performance). Gouraud shading improves on flat shading by removing intensity discontinuities, while Phong shading produces more realistic highlights but requires more computation.
Computer Vision: Shape from Specularities and MotionDamian T. Gordon
The document discusses using specularities and motion to extract surface shape from images. Specifically, it discusses using:
1) Structured highlights from a spherical array of light sources to determine surface orientation of specular surfaces from the detected highlights.
2) Photometric stereo with multiple light source positions to determine surface orientation of both diffuse and specular surfaces.
3) Stereo techniques using highlights detected from multiple camera views to reconstruct the 3D shape of specular surfaces.
Ray tracing is a technique for rendering 3D graphics by simulating the path of light in a scene. It works by casting rays from the viewpoint into the scene and recursively tracing the interactions of the rays with surfaces to determine what is visible. This allows for realistic lighting effects like reflections, refractions, and shadows. The core algorithm works by casting rays for each pixel to calculate the color based on ray intersections with objects, shadows, and simulating effects like reflection and refraction through recursive ray tracing.
Feature based ghost removal in high dynamic range imagingijcga
This paper presents a technique to reduce the ghost artifacts
in a high dynamic range (HDR) image. In HDR
imaging, we need to detect the motion between multiple exp
osure images of the same scene in order to
prevent the ghost artifacts
. First, w
e
establish
correspondences between the aligned reference image and the
other exposure images using the zero
-
mean normalized cross correlation (ZNCC
).
T
hen
, we
find object
moti
on regions
using
adaptive local thresholding of ZNCC feature maps and motion map clustering. In this
process, we focus on finding accurate motion regions and on reducing false detection in order to minimize
the side effects as well.
Through
experiments wit
h several sets of
low dynamic range
images captured with
different exposures, we show that the proposed method can remove the ghost artifacts better than existing
methods
.
Deferred Pixel Shading on the PLAYSTATION®3Slide_N
This document summarizes a deferred pixel shading algorithm implemented on the PlayStation 3 system. The algorithm runs pixel shaders on the Synergistic Processing Elements of the Cell processor concurrently with the GPU for rendering images. Experimental results found that running the pixel shading on 5 SPEs achieved a performance of up to 85Hz at 720p resolution, comparable to running on a high-end GPU. This indicates that the Cell processor can effectively enhance GPU performance by offloading pixel shading work.
The document describes the Phong shading model for modeling specular reflections. It explains that specular reflection results from total or near-total reflection of incident light in a concentrated region around the specular reflection angle. The Phong model sets the intensity of specular reflection proportional to the cosine of the viewing angle raised to a power 'n'. Higher values of 'n' produce shinier surfaces, while lower values produce duller surfaces. The model calculates specular reflection based on vectors representing the light source, viewer, and specular reflection direction.
Interferogram Filtering Using Gaussians Scale Mixtures in Steerable Wavelet D...CSCJournals
An interferogram filtering is presented in this paper. The main concern of the proposed scheme is to lower the residues count mean while preserving the location and jump height of the lines of phase discontinuity. The proposed method is based on a statistical model of the coefficients of multi-scale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian vector and a hidden positive scalar multiplier. Under this model, the Bayesian least squares estimate of each coefficient reduces to a weighted average of the local linear estimates over all possible values of the hidden multiplier variable. The performance of this method substantially has the advantages of reducing number of residuals without affecting line of height discontinuity.
Band Clustering for the Lossless Compression of AVIRIS Hyperspectral ImagesIDES Editor
Hyperspectral images can be efficiently compressed
through a linear predictive model, as for example the one
used in the SLSQ algorithm. In this paper we exploit this
predictive model on the AVIRIS images by individuating,
through an off-line approach, a common subset of bands, which
are not spectrally related with any other bands. These bands
are not useful as prediction reference for the SLSQ 3-D
predictive model and we need to encode them via other
prediction strategies which consider only spatial correlation.
We have obtained this subset by clustering the AVIRIS bands
via the clustering by compression approach. The main result
of this paper is the list of the bands, not related with the
others, for AVIRIS images. The clustering trees obtained for
AVIRIS and the relationship among bands they depict is also
an interesting starting point for future research.
Variable length signature for near-duplicatejpstudcorner
To get this project in ONLINE or through TRAINING Sessions,
Contact:JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83. Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry -9. Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690 , Email: jpinfotechprojects@gmail.com, web: www.jpinfotech.org Blog: www.jpinfotech.blogspot.com
Optic Flow Estimation by Deep Learning outlines several key concepts in optical flow estimation including:
- Optical flow is the apparent motion of brightness patterns in images. Estimating optical flow involves making assumptions like brightness constancy and spatial coherence.
- Classical algorithms like Lucas-Kanade and Horn-Schunck use techniques like regularization, coarse-to-fine processing, and descriptor matching to address challenges like the aperture problem, large displacements, and occlusions.
- Recent deep learning approaches like FlowNet, DeepFlow, and EpicFlow use convolutional neural networks to directly learn optical flow, achieving state-of-the-art performance on benchmarks. These approaches combine descriptor matching, variational optimization,
illumination model in Computer Graphics by irru pychukarsyedArr
The document discusses illumination models used to calculate light intensity on object surfaces in 3D scenes. It describes how surface rendering uses illumination models to determine pixel intensities. Diffuse and specular reflection are explained along with parameters like ambient light, material properties, number of light sources, attenuation, and shadows. Color considerations and transparent surfaces are also covered at a high level.
Neural Scene Representation & Rendering: Introduction to Novel View SynthesisVincent Sitzmann
The document discusses recent advances in novel view synthesis using neural rendering. It describes different approaches for representing 3D scenes like voxel grids, multi-plane images, and implicit functions. Voxel-based methods can render high quality novel views but are memory intensive. Implicit functions enable more compact representations but rendering is slow. Hybrid implicit/explicit and image-based methods provide faster rendering but cannot represent scenes globally. The document outlines open challenges in reducing rendering costs, improving generalization, and enabling new applications in scene understanding.
This paper presents a trifocal Rotman Lens Design
approach. The effects of focal ratio and element spacing on
the performance of Rotman Lens are described. A three beam
prototype feeding 4 element antenna array working in L-band
has been simulated using RLD v1.7 software. Simulated
results show that the simulated lens has a return loss of –
12.4dB at 1.8GHz. Beam to array port phase error variation
with change in the focal ratio and element spacing has also
been investigated.
Este documento presenta una introducción a la simulación de sistemas informáticos. Explica conceptos clave como entidades, eventos, actividades, estados y modelos de simulación. También describe los componentes utilizados en la simulación de sistemas informáticos como servidores, trabajos, estaciones de retardo y sumideros. Finalmente, resume los pasos para realizar un estudio de simulación incluyendo la formulación del problema, objetivos, conceptualización del modelo y colección de datos.
Introduccion a simulacion de sistemas, conceptos, clasificacion de sistemas, clasificacion de modelos, ventajas y desventajas de la simulacion, aplicaciones empresariales simulacion de sistemas, elvis del aguila, elvisdelaguila
El documento presenta una introducción a la simulación de sistemas. Explica que la simulación imita situaciones potenciales para probar experimentos de forma rápida y eficiente. Describe que la simulación de eventos discretos modela sistemas donde las variables cambian en tiempos separados y que requiere definir variables, eventos y distribuciones de probabilidad. Finalmente, menciona que la simulación Monte Carlo es un método computacional que usa números aleatorios para estudiar sistemas matemáticos, físicos u otros mediante muestreo estadí
Unidad 2 ProgramacióN Orientada A Objetos (Repaso)Sergio Sanchez
Este documento explica conceptos básicos de programación orientada a objetos como clases, objetos, encapsulamiento, herencia, interfaces y polimorfismo. Define clases como representaciones abstractas que agrupan atributos y comportamientos comunes, y objetos como instancias concretas de una clase. Explora la implementación de estos conceptos en C# a través de ejemplos.
Este documento describe la simulación de sistemas, incluyendo definiciones de conceptos clave como sistemas, modelos, simulación, ventajas y desventajas. Explica los pasos para realizar un estudio de simulación y proporciona un ejemplo de simulación de un sistema de producción en ProModel con engranes y placas metálicas que pasan por procesos de rectificado, prensado, lavado y empacado.
Introducción a Programación Orientada a Objetos (OOP): Clases y ObjetosKudos S.A.S
La programación orientada a objetos define clases y objetos. Una clase especifica los atributos y métodos de un objeto, mientras que un objeto es una instancia concreta de una clase. Las clases se relacionan entre sí a través de herencia, donde una subclase hereda atributos y métodos de su superclase. El polimorfismo permite que métodos con el mismo nombre tengan comportamientos diferentes dependiendo de la clase del objeto.
What is global illumination and what are the techniques used to combat this problem in real-time applications. Talk briefly covers algorithms like instant radiosity, light propagation volumes and voxel cone tracing. Additional details within the slide notes.
Laser Physics Department -ALNeelain University 5 thGazy Khatmi
The document discusses a new approach for laser surgery and cancer treatment using COMSOL Multiphysics simulation software. Physicians would be able to specify various parameters like tissue type, tumor size, laser properties, and treatment time to simulate scenarios. COMSOL would then be developed into an app for physicians to access and run simulations remotely on their laptops or smartphones. This would allow physicians to interactively plan laser procedures digitally before performing treatments.
This document summarizes an experiment that uses four laser beams to trap thousands of sub-micron polystyrene particles in water, forming an optically induced crystal. Bragg scattering patterns from the crystal agree with the calculated lattice structure and polarization dependence. By observing the decay and rise of Bragg scattering intensity when turning the lattice on and off, the researchers study the Brownian motion dynamics of particles in the periodic potential, finding agreement with simulations based on the Langevin equation.
This document describes research on using near-infrared optical imaging techniques for 3D biological tissue imaging. It discusses diffuse optical tomography (DOT) and fluorescence DOT (F-DOT). For DOT, it covers the photon diffusion equation, forward and inverse models, and finite element method implementation. For F-DOT, it discusses the fluorescence transport equations and parallel inversion schemes. Simulation results using MATLAB and NIRFAST show reconstructed optical property maps and fluorescence distributions in 2D and 3D geometries. Future work aims to further develop 3D imaging software for interfacing with DOT instrumentation.
Seismic data processing 15, kirchhof migrationAmin khalil
Kirchhoff migration is a widely used seismic data processing method. It works by back projecting observed seismic event energy from traces to possible subsurface reflection points based on traveltime. This smears the event energy to all possible subsurface locations, generating artifacts. Stacking multiple migrated traces helps resolve the true dipping reflector. Ray tracing is used to build the traveltime field. Kirchhoff migration is computationally expensive, taking days to process post-stack or months for pre-stack data. Representing the earth in 3D rather than 2D is preferable but requires knowing the 3D velocity model which is challenging.
In this paper we discuss the speckle reduction in images with the recently proposed Wavelet Embedded Anisotropic Diffusion (WEAD) and Wavelet Embedded Complex Diffusion (WECD). Both these methods are improvements over anisotropic and complex diffusion by adding wavelet based bayes shrink in its second stage. Both WEAD and WECD produce excellent results when compared with the existing speckle reduction filters.
This document discusses a method called cone tracing, which is a variant of ray tracing that can be used to render realistic soft shadows and glossy reflections more efficiently than traditional ray tracing. The key aspects are:
- Cone tracing models light as conical volumes rather than individual rays, reducing the number of intersections needed while avoiding noise.
- The paper presents a rendering engine that uses both cone tracing and ray tracing modules to produce shadows and reflections. Cone tracing is used to determine occlusion and reflection colors at ray intersection points.
- Intersection algorithms are approximated for cones, which have linear widening, rather than solved directly through systems of equations like with rays. This achieves accurate results more efficiently
Fusion of Multispectral And Full Polarimetric SAR Images In NSST DomainCSCJournals
Polarimetric SAR (POLSAR) and multispectral images provide different characteristics of the imaged objects. Multispectral provides information about surface material while POLSAR provides information about geometrical and physical properties of the objects. Merging both should resolve many of object recognition problems that exist when they are used separately. Through this paper, we propose a new scheme for image fusion of full polarization radar image (POLSAR) with multispectral optical satellite image (Egyptsat). The proposed scheme is based on Non-Subsampled Shearlet Transform (NSST) and multi-channel Pulse Coupled Neural Network (m-PCNN). We use NSST to decompose images into low frequency and band-pass sub- band coefficients. With respect to low frequency coefficients, a fusion rule is proposed based on local energy and dispersion index. In respect of sub-band coefficients, m-PCNN is used to guide how the fused sub-band coefficients are calculated using image textural information.
The proposed method is applied on three batches of Egyptsat (Red-Green-infra-red) and radarsat2 (C-band full-polarimetric HH-HV and VV-polarization) images. The batches are selected to react differently with different polarization. Visual assessment of the obtained fused image gives excellent information on clarity and delineation of different objects. Quantitative evaluations show the proposed method can superior the other data fusion methods.
This document discusses a reflectance perception model based face recognition algorithm that is robust to illumination variations. It begins with an introduction to the challenges of face recognition across different lighting conditions. It then reviews related work on illumination compensation techniques. The document proposes a reflectance perception model that transforms face images into an illumination-insensitive representation by estimating an illumination gain factor. It also describes applying principal component analysis (PCA) to extract facial features from the preprocessed images in a lower dimensional space, removing unwanted vectors. Finally, it discusses fusing matching scores from multiple classifiers using a weighted sum to improve recognition accuracy across variations in lighting.
This document presents a reflectance perception model based face recognition approach that is robust to illumination variations. It proposes a preprocessing algorithm based on the reflectance perception model to generate illumination insensitive images. It then applies principal component analysis (PCA) for feature extraction to reduce the image dimension and remove unwanted vectors. Multiple classifiers are used to extract features from different Fourier domains and frequencies, and scores from these classifiers are combined using a weighted sum fusion method based on equal error rate weights. Experimental results on standard databases show the proposed approach delivers large performance improvements over other face recognition algorithms in handling illumination variations.
This document discusses the application of remote sensing and geographical information systems in civil engineering. It provides details on topics like resolving power, modulation transfer function, dispersing elements, spectroscopic filters, and types of spectrometers. Resolving power is defined as the minimum distance between two image points that can be detected. It depends on factors like wavelength of light and aperture diameter. The modulation transfer function describes how well an imaging system transfers contrast from the subject to the image. Dispersing elements like prisms and diffraction gratings are used to separate light into spectra. Spectroscopic filters allow only certain wavelength ranges to pass through. And spectrometers are instruments used to measure and record spectra, with types including dispersing and interference
This document provides an overview of digital image processing. It discusses what image processing entails, including enhancing images, extracting information, and pattern recognition. It also describes various image processing techniques such as radiometric and geometric correction, image enhancement, classification, and accuracy assessment. Radiometric correction aims to reduce noise from sources like the atmosphere, sensors, and terrain. Geometric correction geometrically registers images. Image enhancement improves interpretability. Classification categorizes pixels. The document outlines both supervised and unsupervised classification methods.
This document analyzes the polarization and transmission effects of antireflection coatings for silicon-on-insulator (SOI) material systems using simulation software. Without a coating, transmission of transverse magnetic (TM) polarized light is slightly higher than transverse electric (TE) polarized light. A single-layer antireflection coating is designed and optimized to increase average transmission by 19%, reducing the polarization effect. However, multilayer coatings did not further increase transmission over the optimized single layer. In conclusion, antireflection coatings can effectively reduce polarization dependence for SOI materials while improving overall light transmission.
1) Using four laser beams, researchers generated a three-dimensional optical lattice that traps 490nm polystyrene spheres in solution, forming a face-centered orthorhombic crystal structure.
2) The four-beam setup produces a stable periodic potential in all three dimensions that counteracts particle diffusion via radiation pressure balance.
3) Calculations show the four-beam lattice with all beams polarized parallel produces a simple intensity pattern that yields a face-centered orthorhombic crystal structure when the beam angle is 45 degrees.
Digital image processing involves algorithms for transforming digital images. It has many applications including gamma-ray imaging, x-ray imaging, and imaging in visible and infrared bands. In gamma-ray imaging, radioactive isotopes administered to patients emit gamma rays that are detected by sensors to identify tumors. In visible and infrared imaging, examples include using microscopes to examine pharmaceuticals and materials.
UV-visible spectroscopy is a fast analytical technique that measures the absorbance or transmittance of light. Although the UV wavelength ranges from 100–380 nm and the visible component goes up to 800 nm, most of the spectrophotometers have a working wavelength range between 200–1100 nm.
The practical range for UV-vis spectroscopy varies from 200–800 nm; above 800 nm is infrared, while below 200 nm is known as vacuum UV. The ability of matter to absorb and to emit light is what defines its color and the human eye is capable of differentiating up to 10 million unique colors. Light passes through media (transmission), reflects off both opaque and transparent surfaces, and is refracted by crystals. Covalently unsaturated compounds with electronic transition energy differences equivalent to the energy of the UV-visible light absorb at specific wavelengths. These compounds are known as chromophores and are responsible for their color. Covalently saturated groups that do not absorb UV-visible electromagnetic radiation but affect the absorption of chromophore groups are called auxochromes. When UV-vis radiation hits chromophores, electrons in the ground state jump to an excited state, which we refer to as electron-excitation, while auxochromes are electron-donating and have the capacity to affect the color of choromophores while they do not change color themselves. Water and alcohols are mostly transparent and do not absorb in the UV-vis range and so are excellent mediums for UV-visible spectroscopy. Acetone and dimethylformamide (DMF) are good solvents for compounds insoluble in water and alcohol, but they absorb light below 320 and 275 nm, respectively, so are appropriate only above these cut-off wavelengths.
Segmentation Based Multilevel Wide Band Compression for SAR Images Using Coif...CSCJournals
Synthetic aperture radar (SAR) data represents a significant resource of information for a large variety of researchers. Thus, there is a strong interest in developing data encoding and decoding algorithms which can obtain higher compression ratios while keeping image quality to an acceptable level. In this work, results of different wavelet-based image compression and segmentation based wavelet image compression are assessed through controlled experiments on synthetic SAR images. The effects of dissimilar wavelet functions, number of decompositions are examined in order to find optimal family for SAR images. The choice of optimal wavelets in segmentation based wavelet image compression is coiflet for low frequency and high frequency component. The results presented here is a good reference for SAR application developers to choose the wavelet families and also it concludes that wavelets transform is rapid, robust and reliable tool for SAR image compression. Numerical results confirm the potency of this approach.
This document provides an overview of Coherent X-ray Diffraction Imaging (CXDI) and its application to nanostructures. CXDI allows imaging of a sample without using lenses by measuring the diffraction pattern and reconstructing the image using iterative phase retrieval algorithms. The document discusses coherent scattering from finite size crystals, partially coherent illumination, and experimental examples of CXDI for studying crystalline structures at the nanoscale.
Boosting CED Using Robust Orientation Estimationijma
n this paper, Coherence Enhancement Diffusion (CED) is boosted feeding external orientation using new
robust orientation estimation. In CED, proper scale selection is very important as the gradient vector at
that scale reflects the orientation of local ridge. For this purpose a new scheme is proposed in which pre
calculated orientation, by using local and integration scales. From the experiments it is found the proposed
scheme is working much better in noisy environment as compared to the traditional Coherence
Enhancement Diffusion
This document provides an overview of remote sensing and describes its key principles and applications. It defines remote sensing as acquiring information about planetary surfaces from a distance without direct contact. The main components of a remote sensing system are described as the energy source, atmosphere, target interaction, sensor recording, transmission and processing, interpretation and analysis, and applications. Common data types like raster and vector data are also explained. Remote sensing techniques like digital image processing, classification, and analysis are outlined. Examples of satellite imagery and classifications are provided.
Similar to Heckbert p s__adaptive_radiosity_textures_for_bidirectional_r (20)
Este documento presenta varios métodos para encontrar las raíces de una ecuación, incluyendo métodos gráficos, el método de bisección, el método de la falsa posición y el método de punto fijo. Explica cada método a través de ejemplos numéricos y discute criterios para estimar errores y parar los cálculos.
This document provides an overview of Fourier transforms and the fast Fourier transform (FFT) algorithm. It defines the continuous and discrete Fourier transforms, discusses their properties and examples. The FFT is introduced as an efficient algorithm for computing the discrete Fourier transform (DFT) in O(N log N) time rather than O(N2) time. The FFT decomposes the DFT calculation into butterfly operations between stages for inputs in bit-reversed order.
Este documento presenta 10 problemas relacionados con algoritmos de optimización combinatoria y sus complejidades. Los problemas incluyen la mochila, el árbol de mezcla óptimo, el ordenamiento de tareas para minimizar el tiempo medio de espera, y el recubrimiento de vértices y conjuntos. Se proponen estrategias "devoradoras" para cada problema y se analiza si encuentran siempre la solución óptima.
This document provides an overview of global aspects of Mathematica sessions, including:
- Mathematica stores input expressions in In[n] and output expressions in Out[n] to maintain session history.
- Global variables like $Pre and $Post allow inserting functions to manipulate expressions at different stages of evaluation.
- The main loop involves getting input, evaluating it, assigning output, and printing results while applying any relevant global functions.
Oracle b tree index internals - rebuilding the thruthXavier Davias
This document discusses dispelling myths about Oracle B-tree indexes and explaining how they work. It aims to explain how to investigate index internals, how Oracle B-tree indexes are structured and balanced, and when index rebuilds may be appropriate. It provides examples of index structures, headers, entries and updates to prove that indexes are always balanced and efficient without needing rebuilds in most cases.
El documento describe el enfoque de sistemas para la planeación. El enfoque de sistemas considera que un sistema está compuesto de elementos que interactúan para lograr un objetivo común. El proceso de solución de problemas usando este enfoque incluye tres subsistemas: 1) formulación del problema, 2) identificación y diseño de soluciones, y 3) control de resultados. Este enfoque es útil para abordar problemas complejos que involucran múltiples factores interrelacionados.
El documento discute el problema del anumerismo o incapacidad para manejar conceptos numéricos y probabilísticos de manera adecuada. Presenta varios ejemplos de cómo personas cultas cometen errores al razonar sobre números grandes y probabilidades pequeñas. El autor argumenta que una mejor comprensión de conceptos matemáticos ayudaría a las personas a evaluar mejor riesgos comunes y noticias exageradas.
Este documento presenta conceptos básicos de programación paralela en GPU. Explica conceptos como paralelismo, distribución de datos, reducciones y condiciones de carrera. Luego, introduce herramientas para programar en GPU, incluyendo compilación de código CUDA a PTX y enlazado con librerías CUDA. Finalmente, provee ejemplos ilustrativos de diferentes estrategias de programación paralela en GPU.
El documento describe los objetivos del sistema de gestión de memoria en un sistema operativo, incluyendo proporcionar a cada proceso un espacio lógico independiente, proteger la memoria entre procesos, y maximizar el rendimiento del sistema. También discute cómo el sistema operativo y el hardware trabajan juntos para traducir las direcciones lógicas de los procesos a direcciones físicas de memoria y proporcionar protección entre procesos.
(1) El documento trata sobre el control de procesos y la sincronización en sistemas operativos multiprogramados.
(2) Los procesos compiten por recursos compartidos como la CPU y requieren mecanismos de sincronización para coordinar el acceso a estos recursos.
(3) El sistema operativo representa los procesos mediante bloques de control de proceso (PCB) y los gestiona usando colas de procesos en diferentes estados.
Este documento introduce los sistemas distribuidos. Primero, describe la evolución de los sistemas de cómputo desde los sistemas de lotes hasta los sistemas distribuidos. Luego, define un sistema distribuido como un conjunto de computadoras interconectadas que comparten estado y ofrecen una visión de sistema único. Finalmente, discute cómo los protocolos de red y el middleware ocultan la distribución física de los recursos para proporcionar transparencia.
Este documento describe los multiprocesadores y el problema de la coherencia de cachés en sistemas con memoria compartida. Los multiprocesadores tienen varios procesadores que funcionan de forma paralela e independiente compartiendo el mismo espacio de direccionamiento de memoria. El problema de coherencia surge cuando diferentes procesadores acceden a la misma localización de memoria a través de cachés separadas, lo que puede dar lugar a lecturas inconsistentes de los valores almacenados. Se analizan varios protocolos para mantener la coherencia entre las cachés de los diferentes pro
Este documento presenta una introducción a las arquitecturas avanzadas de computación paralela. Explica diferentes clasificaciones de sistemas paralelos, fuentes de paralelismo, y métricas para medir el rendimiento de sistemas paralelos. También describe arquitecturas como procesadores vectoriales, procesadores matriciales, redes de interconexión, y multiprocesadores.
Este documento presenta un trabajo de graduación sobre memoria distribuida compartida. El trabajo describe el origen y conceptos de la memoria distribuida compartida, diseños e implementaciones de hardware y software para este tipo de memoria, y presenta un caso de estudio sobre un sistema de memoria distribuida compartida de HP. El trabajo busca obtener el título de Ingeniero en Ciencias y Sistemas de la Universidad de San Carlos de Guatemala.
Este documento presenta un resumen de 3 oraciones de una tesis doctoral sobre computación paralela y entornos heterogéneos. La tesis estudia paradigmas como maestro-esclavo y pipeline para sistemas heterogéneos, desarrollando modelos analíticos, herramientas y validaciones. El documento contiene una introducción al contexto, objetivos y metodología, así como capítulos sobre maestro-esclavo, pipeline y una aplicación de predicción de estructura de RNA.
Este documento describe los objetivos del sistema de gestión de memoria, incluyendo la creación de espacios lógicos independientes para cada proceso, la protección entre procesos, y la compartición de memoria para soportar procesos ligeros. También explica los esquemas de reubicación de direcciones lógicas a físicas mediante hardware o software para lograr estos objetivos.
Este documento presenta 5 ejercicios sobre el tema de entrada/salida. El primer ejercicio calcula el tiempo de acceso a un sector de disco. El segundo ejercicio pide escribir un programa en ensamblador para controlar un semáforo. El tercer ejercicio calcula la sobrecarga de procesamiento de interrupciones de un ratón. Los ejercicios 4 y 5 piden escribir programas en ensamblador para controlar dispositivos de entrada/salida como sensores y alarmas.
Este documento presenta 9 ejercicios sobre memoria caché y memoria virtual. Los ejercicios cubren temas como el cálculo del tiempo medio de acceso a memoria considerando la tasa de aciertos de la caché, el cálculo de tasas de fallos para diferentes configuraciones de caché como directa, asociativa y por conjuntos, y el análisis de fragmentos de código. También incluye ejercicios sobre paginación virtual como el formato de direcciones virtuales, el número de páginas y el cálculo de direcciones
Este documento presenta 4 ejercicios sobre la arquitectura y funcionamiento de un procesador de 32 bits. El primer ejercicio pide identificar las operaciones elementales de la instrucción lw R1, (R2) y calcular la cantidad de instrucciones que puede ejecutar el procesador en 1 segundo. El segundo ejercicio pide identificar las operaciones elementales y la instrucción máquina correspondiente a una secuencia de señales de control dadas. El tercer ejercicio describe la estructura de un procesador y pide identificar las operaciones elementales de la
El documento presenta 4 ejercicios sobre formatos de instrucciones y direccionamiento en computadores. El primer ejercicio pide indicar el formato de la instrucción ADDV R1, R2, M para un computador de 16 bits. El segundo ejercicio describe un computador de 32 bits y pide detalles sobre la instrucción SWAPM. El tercer ejercicio pide diseñar el formato de instrucciones para un computador de 32 bits con 115 instrucciones. El cuarto ejercicio describe instrucciones para un computador de 16 bits y pide detalles sobre un fragment
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
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* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
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We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
2. O SIGGRAPH '90, Dallas, August 6-10, 1990
diffuse roughspecular ideal specular
Figure 1: Three classes of reflectance: diffuse, rough specular,
and ideal specular; showing a polar plot of the reflectance coeffi-
cient for fixed incoming direction and varying outgoing direction.
Transmittance is similar.
A diffuse surface appears equally bright from all viewing di-
rections, but a specular surface's brightness varies with viewing
direction, so we say that diffuse interaction is view-independent
while specular interaction is view-dependent. The simplest ma-
terials have a position-invariant, isotropic BDF consisting of a
linear combination of diffuse and ideal specular interaction, but
a fully-general BDF can simulate textured, anisotropic, diffuse
and rough specular surfaces.
2.1 Ray Tracing vs. l:tadiosity
The two most popular algorithms for global illumination are ray
tracing and radiosity. Ray tracing is both a visibility algorithm
and a shading algorithm~ but radiosity is just a shading algo-
rithm.
2.1.1 Ray Tracing
Classic ray tracing generates a picture by tracing rays from the
eye into the scene, reeursively exploring specularly reflected and
transmitted directions, and tracing rays towaxd point light sources
to simulate shadowing [Whitted80]. It assumes that the BDF
contains no rough specular, and that the incident light relevant
to the diffuse computation is a sum of delta functions in the di-
rection of each light source. This latter assumption implies a
local illumination model for diffuse.
A more realistic illumination model includes rough specular
BDF's and computes diffuse interaction globally. Exact simu-
lation of these effects requires the integration of incident light
over cones of finite solid angle. Ray tracing can be generalized
to approximate such computations using distribution ray trac-
ing [Cook84], ILee85], [Dippe85], [Cook86], [Kajiya86]. (We pro-
pose the name "distribution ray tracing" as an alternative to
the current name, "distributed ray tracing", which is confusing
because of its parallel hardware connotations.) In distribution
ray tracing, rays are distributed, either uniformly or stochasti-
cally, throughout any distributions needing integration. Many
rays must be traced to accurately integrate the broad reflectance
distributions of rough specular and diffuse surfaces: often hun-
dreds or thousands per surface intersection.
2.1.2 Radiosity
The term radiosity is used in two senses. First, radiosity is a
physical quantity equal to power per unit area, which determines
the intensity of light diffusely reflected by a surface, and second,
radiosity is a shading algorithm. The meaning of each use should
be clear by context.
The Classic radiosity algorithm subdivides each surface into
polygons and determines the fraction of energy diffusely radi-
ated from each polygon to every other polygon: the pair's form
]actor. From the form factors, a large system of equations is
constructed whose solution is the radiosities of each polygon
[SiegelS1], [Gora184], [Nishita85]. This system can be solved ei-
ther with Gauss-Seidel iteration or, most conveniently, with pro-
gressive techniques that compute the matrix and solve the sys-
tem a piece at a time [Cohen88]. Form factors can be determined
analytically for simple geometries [Siege181], [Baum89], but for
complex geometries a numerical approach employing a visibility
algorithm is necessary. The most popular visibility method for
this purpose is a hemicube computed using a z-buffer [Cohen85],
but ray tracing has recently been promoted as an alternative
[Wallace89], [Sillion89]. Classic radiosity assumes an entirely dif-
fuse reflectance, so it does not simulate specular interaction at
all.
The output of the radiosity algorithm is one radiosity value
per polygon. Since diffuse interaction is by definition view-inde-
pendent, these radiosities are valid from any viewpoint. The
radiosity computation must be followed by a visibility algorithm
to generate a picture.
The radiosity method can be generalized to simulate specu-
lar interaction by storing not just a single radiosity value with
each polygon, but a two-dimensional array [Imme186], [Shao88],
[Buckalew89]. The resulting algorithm, which we call directional
radiosity, simulates both diffuse and specular interaction globally,
but the memory requirements are so excessive as to be impracti-
cal.
2.1.3 Hybrid Methods
Ray tracing is best at speculax and radiosity is best at diffuse,
and the above attempts to generalize ray tracing to diffuse and
to generalize radiosity to specular stretch the algorithms beyond
the reflectance realms for which each is best suited, making them
less accurate and less efficient. Another class of algorithms is
formed by hybridizing the methods, using a two-pass algorithm
that applies a radiosity pass followed by the ray tracing pass.
This is the approach used by [Wallace87] and [Sillion89].
The first pass of Wallace's algorithm consists of classic radios-
ity extended to include diffuse-to-diffuse interactions that bounce
off planar mirrors. He follows this with a classic ray tracing pass
(implemented using a z-buffer). Unfortunately, the method is
limited to planar surfaces (because of the polygonization involved
in the radiosity algorithm) and to perfect planar mirrors.
Sillion's algorithm is llke Wallace's but it computes its form
factors using ray tracing instead of hemicubes. This eliminates
the restriction to planar mirrors. The method still suffers from
the polygonization inherent in the radiosity step, however.
2.2 Sampling Radlositles
Many of the sampling problems of ray tracing have been solved
by recent adaptive algorithms [WhittedS0], [Cook86], [Lee85],
[Dippe85], [Mitchel187], [Painter89], particularly for the simula-
tion of specular interaction. The sampling problems of the radios-
ity algorithm are less well studied, probably because its sampling
process is less explicit than that of ray tracing.
146
3. ~' ComputerGraphics,Volume24, Number4, August1990
We examine four data structures for storing radiosities: light
images, polygons, samples in 3-D, and textures. Several different
algorithms have been used to generate these data structures: ra-
diosities have been generated analytically, with hemicubes at the
receiver (gathering), with hemieubes at the sender (shooting),
and by tracing rays from the eye or from the light.
2.2.1 Light Images
The simplest data structure, the light image, simulates only shad-
ows, the first order effects of diffuse interreflection. Light images
are pictures of the scene from the point of view of each light
~ource. They are most often generated using the z-buffer shadow
algorithm, which saves the z-buffers of these light images and
uses them while rendering from the point of view of the eye to
test if visible points are in shadow [Wilhams78], [Reeves87]. This
shadow algorithm is more flexible than most, since it is not lim-
ited to polygons, but it is difficult to tune. Choosing the resolu-
tion for the light images is critical, since aliasing of shadow edges
results if the light images are too. coarse.
2.2.2 Polygonlzed l~adioslty
The Atherton-Weiler algorithm is another method for comput-
ing shadows that renders from the point of view of the lights
[Atherton78]. It uses the images rendered from the lights to gen-
erate "surface detail polygons", modifying the scene description
by splitting all polygons into shadowed and unshadowed portions
that are shaded appropriately in the final rendering from the eye.
Surface detail polygons are an example of polygonized radiosity,
the storage of radiosity as polygons. The shadows computed by
the Atherton-Weiler algorithm are a first-approximation to the
interrefiection simulated by radiosity algorithms.
The most common method for computing polygonized radios-
ity is, of course, the classic radiosity algorithm. A major prob-
lem with this Mgorithm is that surfaces are polygonized before
radiosities are computed. Difficulties result if this polygonization
is either too coarse or too fine.
Sharp shadow edges caused by small light sources can be un-
dersampled if the polygonization is too coarse, resulting in blur-
ring or abasing of the radiosities. Cohen developed the "sub-
structuring" technique in response to this problem [Cohen86].
It makes an initial pass computing radiosities at low resolution,
then splits polygons that appear to be in high-variance regions
and recomputes radiosities. Substructuring helps, but it is not
fully automatic, as the subdivision stopping criterion appears to
be a polygon size selected in some ad hoc manner. The limi-
tations of the method are further demonstrated by the absence
to date of radiosity pictures in published work exhibiting sharp
shadow edges.
The other extreme of radiosity problems is oversampling of
radiosities due to polygonization that is too fine for the hemicube.
The resulting quantization can be cured by adaptive subdivision
of the hemicube or of the light rays [Wallace89], [Baum89].
We conclude that polygonization criteria remain a difficult
problem for the radiosity method.
It is interesting to note the similaxities between radiosity al-
gorithms and the Atherton-Weiler algorithm. Conceptually, the
original radiosity method gathers light to each polygon by ren-
dering the scene from the point of view of each receiver, but
the progressive radiosity algorithm shoots light by rendering the
scene from the point of view of each sender (a light source). A
progressive radiosity algorithm using a hemicube is thus much
like repeated application of the Atherton-Weiler shadow algo-
rithm.
2.2.3 Samples in 3-D
l~adiosities can be computed using brute force distribution ray
tracing [Kajiya86], but the method is inefficient because it sam-
ples the slowly-varying radiosity function densely. To exploit the
coherence of radiosity values, Ward sampled the diffuse compo-
nent sparsely, and saved this information in a world space octree
[Ward88]. Because his algorithm shot rays from the eye toward
the lights, and not vice-versa, it had difficulty detecting light
sources reflected by specular surfaces.
2.2.4 Radiosity Texture
The fourth data structure for radiosities is the radiosity texture.
Instead of polygonizing each surface and storing one radiosity
value per polygon, radiosity samples are stored in a texture on
every diffuse surface in the scene [Arvo86]. Arvo called his tex-
tures "illumination maps". He computed them by tracing rays
from the light sources.
2.3 Light Ray Tracing
Rays traced from the eye we call eye rays and rays traced from the
lights we call light rays. We avoid the terms "forward ray tracing"
and "backward ray tracing" because they are ambiguous: some
people consider photon motion ~'forward', while others consider
Whitted's rays "forward".
Light ray tracing was originally proposed by Appel [Appe168],
who "stored" his radiosities on paper with a plotter. Light ray
tracing was proposed for beams in previous work with Hanra-
han [Heckbert84] where we stored radiosities as surface detail
polygons like Atherton-Weiler. This approach was modified by
Strauss, who deposited light directly in screen pixels when a dif-
fuse surface was hit by a beam, rather than store the radiosities
with the surface [Strauss88]. Watt has recently implemented light
beam tracing to simulate refraction at water surfaces [Wattg0].
Arvo used light ray tracing to compute his radiosity textures
[Arvo86]. Light ray tracing is often discussed but has been little
used, to date.
3 Bidirectional Ray Tracing Using Adap-
tive Radiosity Textures
In quest of realistic image synthesis, we seek efficient algorithms
for simulating global illumination that can accommodate curved
surfaces, complex scenes, and arbitrary surface characteristics
(BDF's), and generate pictures perceptually indistinguishable
from reality. These goals are not realizable at present, but we
can make progress if we relax our requirements.
147
4. O SIGGRAPH '90, Dallas, August 6-10, 1990
We make the following assumptions:
(1) Only surfaces are relevant. The scattering or absorp-
tion of volumes can be ignored.
(2) Curved surfaces are important. The world is not
polygonal.
(3) Shadows, penumbras, texture, diffuse interreflection,
specular reflection, and refraction are all important.
(4) We can ignore the phenomena of fluorescence (light
wavelength crosstalk), polarization, and diffraction.
(5) Surface properties can be expressed as a linear com-
bination of diffuse and specular reflectance and trans-
mission functions:
BDF =kd~BRDFdity + ksrB1~DF~pec+
kdtBTDFdi// + kstBTDFspec
The coet-ficients klj are not assumed constant.
(6) Specular surfaces are not rough; all specular interac-
tion is ideal.
3.1 Approach
Our approach is a hybrid of radiosity and ray tracing ideas.
Rather than patch together these two Mgorithms, however, we
seek a simple, coherent, hybrid algorithm. To provide the great-
est generality of shape primitives and optical effects, we choose
ray tracing as the visibility algorithm. Because ray tracing is
weak at simulating global diffuse interaction, the principal task
before us is therefore to determine an etficient method for calcu-
lating radiosities using ray tracing.
To exploit the view-independence and coherence of radiosity,
we store radioslty with each diffuse surface, using an adaptive
radiosity texture, or rex. A rex records the pattern of light and
shadow and color bleeding on a surface. We store radiosity as
a texture, rather than as a polygonization, in order to decouple
the data structures for geometry and shading, and to facilitate
adaptive subdivision of radieslty information; and we store it
with the surface, ratlier than in a global octree [Ward88], or in a
light image, based on the intuition that radiosities are intrinsic
properties of a surface. We expect that the memory required for
rexes will not be excessive, since dense sampling of radiosity will
be necessary only where it has a high gradient, such as at shadow
edges.
Next we need a general technique for computing the rexes.
The paths by which photons travel through a scene can motivate
our algorithm (figure 2). We can characterize each interaction
along a photon's path from light (L) to eye (E) as either diffuse
(D) or specular (S). Each path can therefore be labeled with
some string in the set given by the regular expression L(D]S)*E.
Classic ray tracing simulates only LDS*E [LS*E paths, while
classic radioslty simulates only LD*E. Eye ray tracing has dif-
ficulty finding paths such as LS+DE because it doesn't know
where to look for specularly reflected light when integrating the
hemisphere. Such paths are easily simulated by light ray tracing,
however.
We digress for a moment to discuss units. Light rays carry
power (energy/time) and eye rays carry intensity (energy / (time
* projected area * solid angle)). Each light ray carries a fraction
Figure 2: Selected photon paths from light (L) to eye (E) by
way of diffuse (D) and specular (S) surfaces. For simplicity, the
surfaces shown are entirely diffuse or entirely specular; normally
each surface would be a mixture.
D
° /
Figure 3: Left: first level light ray tracing propagates photons
from the light to the first diffuse surface on a path (e.g. LD
and LSD); higher levels of progressive light ray tracing simulate
indirect diffuse interaction (e.g. LDD). Right: eye ray trac-
ing shoots rays from the eye, extracting radiosities from diffuse
surfaces (e.g. it traces DE and DSE in reverse).
of the total power emitted by the light.
We can simulate paths of the form LS*D by shooting light
rays (photons) into the scene, depositing the photon's power into
the rex of the first diffuse surface encountered (figure 3, left).
Such a light ray tracing pass will compute a first approximation
to the radiosities. This can be followed by an eye ray tracing pass
in which we trace DS*E paths in a backward direction, extract-
ing intensity from the rex of the first diffuse surface encountered
(figure 3, right). The net effect of these two passes will be the
simulation of all LS*DS*E paths. The rays of the two passes
"meet in the middle" to exchange information. To simulate dif-
fuse interreflection, we shoot progressively from bright surfaces
[Cohen88] during the light ray tracing pass, thereby accounting
for all paths: L(S*D)*S*E = L(D[S)*E. We call these two
passes the light pass and eye pass. Such bidirectional ray tracing
using adaptive radiosity textures can thus simulate all photon
paths, in principle.
Our bidirectional ray tracing algorithm is thus a hybrid. From
radiosity we borrowed the idea of saving and reusing the diffuse
component, whicil is view-independent, and from ray tracing we
borrowed the idea of discarding and recomputing the specular
component, which is view-dependent.
148
5. ~ ComputerGraphics,Volume24, Number4, August1990
3.2 All Sampling is Adaptive
There are three separate multidimensional sampling processes
involved in this approach: sampling of directions from the light,
sampling of directions from the eye (screen sampling), and sam-
pling of radiosity on each diffuse surface.
3.3 Adaptive Radiosity Textures (Rexes)
Rexes are textures indexed by surface parameters u and v, as in
standard texture mapping [Blinn76], [Heckbert86]. We associate
a rex with every diffuse or partially-diffuse surface. By using
a texture and retaining the initial geometry, instead of polygo-
nizing, we avoid the polygonized silhouettes of curved surfaces
common in radiosity pictures.
In the bidirectional ray tracing algorithm, the rexes collect
power from incident photons during the light pass, and this in-
formation is used to estimate the true radiosity function during
the eye pass (figure 4). Our rexes thus serve much like den-
sity estimators that estimate the probability density of a random
variable from a set of samples of that random variable [Silver-
man86]. Density can be estimated using either histogram meth-
ods, which subdivide the domain into buckets; or kernel estima-
tors, which store every sample and reconstrnct the density as a
sum of weighted kernels (similar to a spline).
The resolution of a rex should be related to its screen size.
Ideally, we want to resolve shadow edges sharply in the final
picture, which means that rexes should store details as fine as
the preimage of a screen pixel. On the other hand, resolution
of details smaller than this is unnecessary, since subpixel detail
is beyond the Nyquist limit of screen sampling. Cohen's sub-
structuring technique is adaptive, but its criteria appear to be
independent of screen space, so it cannot adapt and optimize the
radiosity samples for a particular view.
To provide the light pass with information about rex resolu-
tion we precede the light pass with a size pass in which we trace
rays from the eye, labeling each diffuse surface with the minimum
rex feature size.
3.8.1 Adaptive Light Sampling
Adaptive sampling of light rays is desirable for seYeral reasons.
Sharp resolution of shadow edges requires rays only where the
light source sees a silhouette. Also, it is only necessary to trace
light paths that hit surfaces visible (directly or indirectly) to the
eye. Thirdly, omnidirectional lights disperse photons in a sphere
of directions, but when such lights are far from the visible scene,
as is the sun, the light ray directions that affect the final picture
subtend a small solid angle. Finally, stratified sampling should be
used for directional lights to effect their goniometric distribution.
Thus, to avoid tracing irrelevant rays, we sample the sphere of
directions adaptively [Sillion89], [Wallace89].
For area light sources, we use stratified sampling to distribute
the ray origins across the surface with a density proportional to
the local radiosity. Stratified sampling should also be used to
shoot more light rays near the normal, since it is intensity that
is constant with outgoing angle, while power is proportional to
the cosine of the angle with the normal. If the surface has both a
standard texture and a rex mapped onto it, then the rex should
be modulated by this standard texture before shooting. With
Figure 4: Photons incident on a rex (shown as spikes with height
proportional to power) are samples from the true, piecewise-
continuous radiosity function (the curve). We try to estimate
the function from the samples.
area light sources, the distribution to be integrated is thus four-
dimensional: two dimensions for surface parameters u and v,
and two dimensions for ray direction. For best results, a 4-D
data structure such as a k-d tree should be used to record and
adapt the set of light rays used.
3.3.2 Adaptive Eye Sampling
Eye rays (screen pixels) are sampled adaptively as well. Tech-
niques for adaptive screen sampling have been covered well by
others [Warnock69], [Whitted80], [Mitchell87], [Painter89].
3.4 Three Pass Algorithm
Our bidirectional ray tracing algorithm thus has three passes.
We discuss these passes here in a general way; the details of a
particular implementation are discussed in §4. The passes are:
size pass - record screen size information in each rex
light pass - progressively trace rays from lights and bright
surfaces, depositing photons on diffuse surfaces to
construct radiosity textures
eye pass - trace rays from eye, extracting light from dif-
fuse surfaces to make a picture
Specular reflection and transmission bounces are followed on all
three passes. Distribution ray tracing can be used in all passes
to simulate the broad distributions of rough specular reflections
and other effects.
3.4.1 Size Pass
As previously described, the size pass traces rays from the eye,
recording information about the mapping between surface pa-
rameter space and screen space. This information is used by each
rex during the light pass to terminate its adaptive subdivision.
3.4.2 Light Pass
Indirect diffuse interaction is simulated during the llght pass by
regarding bright diffuse surfaces as light sources, and shooting
light rays from them~ as in progressive radiosity. The rex records
the shot and unshot power.
149
6. @SIGGRAPH '90, Dallas, August 6-10, 1990
The adaptive algorithm for light ray tracing must ensure that:
(a) a minimum level of light sampling is achieved; (b) more rays
are devoted near silhouettes, shadows, and high curvature areas;
(c) sharp radiosity gradients are resolved to screen pixel size; and
(d) light rays and rexes are subdivided cooperatively.
3.4.3 Eye Pass
The eye pass is like a standard ray tracing algorithm except that
the diffuse intensity is extracted out of the text instead of from a
shadow ray. The radiosity of a surface patch is its power divided
by its world-space surface area.
After the three passes are run, one could move the eye point
and re-run the eye pass to generate other views of the seen% but
the results would be inferior to those made by recomputing the
rexes adapted to the new viewpoint.
3.4.4 Observations
Because light rays are concentrated on visible portions of the
scene and radlosity is resolved adaptive to each surface~s projec-
tion in screen space, the radiosity calculation performed in the
light pass is view-dependent. But this is as it should be: al-
though the exact radiosity values are view-independent, the ra-
diosity sample locations needed to make a picture are not. When
computing moving-camera animation~ one could prime the rexes
by running the size pass for selected key frames to achieve more
view-independent sampling.
4 Implementation and Results
The current implementation realizes many, but not all, of the
ideas proposed here. It performs bidirectional ray tracing using
adaptive sampling for light~ eyed and rex. It has no size pass e
just a light pass and an eye pass. The program can render scenes
consisting of CSG combinations of spheres and polyhedra. Spec-
ular interaction is assumed ideal, and diffuse transmission is not
simulated. The light pass shoots photons from omnidirectional
point light sources, and does not implement progressive radios-
ity. The implementation thus simulates only iS*DS*E paths at
present. We trace ray trees, not just ray paths [Kajiya86].
4.0.5 Data Structures
Quadtrees were used for each of the 2-D sampling processes
[Samet90]: one for the outgoing directions of each light, one for
the parameter space of each radiosity texture, and one for the
eye.
The light and eye quadtrees are quite similar; their records
are shown below in pseudocode. Each node contains pointers to
its child nodes (if not a leaf) and to its parent node. Light space
is parameterized by (r,s), where r is latitude and s is longitude.
and eye space (screen space) is parameterized by (x,y). Each
node represents a square region of the parameter space whose
corner is given by (to, so) or (x0, y0) and whose size is propor-
tional to 2 -level.
low
Figure 5: I~ex quadtree on a surface. Adaptive fez subdivision
tries to subdivide more finely near a shadow edge.
The light quadtree sends one light ray per node at a location
uniformly distributed over the square. Also stored in each light
quadtree node is the ID of the surface hit by the light ray, if any,
and the surface parameters (u, v) at the intersection point. This
information is used to determine the distance in parameter space
between rex hits.
Eye quadtrees are simpler. Each node has pointers to the
intensities at its corners. These are shared with neighbors and
children. Eye ray tracing is currently uniform, not stochastic.
A rex quadtree node represents a square re,on of (u, v) pa-
rameter space on a diffuse surface (figure 5). Leaves in the rex
quadtree act as histogram buckets~ accumulating the number of
photons and their power. Rex nodes also record the world space
surface area of their surface patch.
lisht_node: type =
record
leaf: boolean;
mark: boolean;
level: int;
parent: "lisht_node;
nw, ne, se, ss: "light_node;
tO, sO: real;
r~ e: real;
surfnc: int;
u, v: real;
end;
eye_node: type =
record
leaf: boolean;
mark: boolean;
level: int;
parent: "eye_node;
nw, ne. se, sw: "eye_node;
xO. yO: real;
inw. ine. ise. is,: "color;
end;
{LIGHT QUADTREE NODE>
{is this a leaf?>
{should node be split?}
{level in tree (rook=O)}
{parent node. if any}
{four child/sn, if not a leaf}
{params of corner of square}
{dir. params o2 ray (lat.lon)}
{id of surface hit. if any}
{surf params of surface hit}
{EYE QUADTREE NODE}
{is this a leaf?}
{should node be split?}
{level in tree (root=O)}
{parent node. if any}
{four children, if not a leaf}
{coords of corner of square}
{intensity samples at corners}
rex_node: type =
record
leaf: boolean;
mark: boolean;
level: int;
parent: "rex_node;
nw, ne, se, sw: "rex_node;
nO. vO: real;
area: real;
count: int;
power: color;
end;
{REX QUADTREENODE}
{is this a leaf?}
{should node be split?}
{level in tree (root=O)}
{parent node. if any}
{four children, if not a leaf}
{surf params of square corner}
{surface area of this bucket}
{~photon~ in bucket, if leaf}
{accumulated power of bucket}
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7. ~ ComputerGraphics,Volume24, Number4, August1990
1/16 1/16...
O0 i! 0
• • 0 o
Figure 6: Light quadtree shown schematically (left) and in light
direction parameter space (right). When a light quadtree node is
split, its power is redistributed to its four sub-nodes, which each
send a ray in a direction (r,s) jittered ~oithin their parameter
square. The fractional power of each light ray is shown next to
the leaf node that sends it.
The current implementation uses the following algorithm.
4.1 Light Pass
First, rex quaxitrees are initialized to a chosen starting level (level
3, say, for 8x8 subdivision), and the counts and powers of all
leaves are zeroed.
For each light, light ray tracing proceeds in breadth first order
within the light quadtree, at level 0 tracing a single ray carrying
the total power of the light, at level 1 tracing up to 4 rays, at level
2 tracing up to 16 rays, etc (figure 6). At each level, we adaptively
subdivide both the light quadtree and the rex quadtrees. Chang-
ing the rex quadtrees in the midst of light ray shooting raises
the histogram redistribution problem, however: if a histogram
bucket is split during collection, it is necessary to redistribute
the parent's mass among the children. There is no way to do this
reliably without a priori knowledge, so we clear the rex at the
beginning of each level and reshoot.
Processing a given level k of light rays involves three steps:
(1) rex subdivision to split rex buckets containing a high density
of photons, (2) light marking to mark light quadtree nodes where
more light rays should be sent, and (3) light subdivision to split
marked light nodes.
Rex subdivision consists of a sweep through every rex quadtree
in the scene, splitting all rex buckets whose photon count exceeds
a chosen limit. All counts and powers are zeroed at the end of
this sweep.
Light marking traverses the light quadtree, marking all level
k nodes that meet the subdivision criteria listed below.
(1) Always subdivide until a minimum level is reached.
(2) Never subdivide beyond a maximum level (if a size
pass were implemented, it would determine this max-
imum level locally).
Otherwise, look at the light quadtree neighbors above, below,
left, and right, and subdivide if the following is true:
(3) The ray hit a diffuse surface, and one of the four
neighbors of the rex node hit a different surface or
was beyond a threshold distance in (u, v) parameter
space from the center ray's.
To help prevent small feature neglect, we also mark for subdi-
vision all level k - 1 leaves that neighbor on level k leaves that
are m~ked for subdivision. This last rule guarantees a restricted
quadtree [Von Herzen87] where each leaf node's neighbors are at
a level within plus or minus one of the center node's.
Light subdivision traverses the light quadtree splitting the
marked nodes. Subdividing a node splits a ray of power p into
four rays of power p/4 (figure 6). When a light node is cre-
ated (during initialization or subdivision) we select a point at
random within its square (r, s) domain to achieve jittered sam-
pling [Cook86] and trace a ray in that direction. Marked nodes
thus shoot four new rays, while unmarked nodes re-shoot their
rays. During light ray tracing we follow specular bounces, split-
ting the ray tree and subdividing the power according to the re-
flectance/transmittance coefficients kij, and deposit their power
on any diffuse surface that are hit. When a diffuse surface is hit,
we determine (u,v) of the intersection point, and descend the
surface's rex quadtree to find the rex node containing that point.
The power of that node is incremented by the power of the ray
times the cosine of the incident angle.
4.2 Eye Pass
The eye pass is a fairly standard adaptive supersampling ray
tracing algorithm: nodes are split when the intensity difference
between the four corners exceeds some threshold. To generate a
picture, nodes larger than a pixel perform bilinear interpolation
to fill in the pixels they cover, while nodes smaller than a pixel
are averaged together to compute a pixel. The picture is stored
in floating point format initially, then scaled and clamped to the
range [0,255] in each channel.
4.3 Results
Figures 7-12 were generated with this program. Figures 7, 8, and
9 show the importance of coordinating the light ray sampling pro-
cess with the rex resolution. Sending too few light rays results
in a noisy radiosity estimate from the rex, and too coarse a rex
results in blocky appearance. When the rex buckets are approxi-
mately screen pixel size and the light ray density deposits several
photons per bucket (at least 10, s~y), the results are satisfac-
tory. We estimate the radiosity using a function that is constant
within each bucket; this simple estimator accounts for the blocki-
ness of the images. If bilinear interpolation were used, as in most
radiosity algorithms, we could trade off blockiness for blurriness.
Figure 10 shows adaptive subdivision of a rex quadtree, split-
ting more densely near shadow edges (the current splitting cri-
teria cause unnecessary splitting near the border of the square).
Its rex quadtree is shown in figure 11.
Figure 12 shows off some of the effects that are simulated by
this algorithm.
151
8. SIGGRAPH '90, Dallas, August 6-10, 1990
.7~:~"Z :" : •
I • ":J'g
Lgm":+ .... z2q " .4:!
Figure 7: Noisy appearance results when too few light rays are
received in each rex bucket (too few light rays or too fine a rex).
Scene consists of a diffuse sphere above a diffuse floor both illu-
minated by an overhead light source.
Figure 8: Blocky or blurry appearance results when rex buckets
are much larger than a screen pixel (too coarse a rex).
Figure 9: Proper balance of light sampling and rex sampling
reduces both noise and blockiness.
Figure 10: Rez with adaptation: the rex of the floor is initially a
single bucket, but it splits adaptively near the edges of the square
and near the shadow edge.
Statistics for these images are listed below, including the
number of light rays, the percentage of light rays striking an ob-
ject, the resolution of the rex, the resolution of the final picture,
the number of eye rays, and the CPU time. All images were com-
puted on a MIPS R2000 processor. The lens image used about 20
megabytes of memory~ mostly :for the light qu~dtree. Ray trees
were traced to a depth of 5.
#LRAYS %HIT REX I EYE #ERAYS
87,400 10% 128~ I 256~ 246,000
87,400 10% 82 2562 139,000
822,000 68% 1282 2562 146,000
331,000 20% vbl 2562 139,000
1,080,000 61% 256~ 5122 797,000
TIME I FIG1.0 min. fig. 7
0.6 rain. fig. 8
3.5 rain. fig. 9
1.3 rain. fig. 10
6.4 rain. fig. 12
152
9. ~ ComputerGraphics,Volume24, Number4, August1990
Figure 11: Rex quadtree in (u, v) space of previous figure's floor.
Each leaf node's square is colored randomly. Note the subdivision
near the shadow edge and the quadtree restriction.
5 Conclusions
The bidirectional ray tracing algorithm outlined here appears to
be an accurate, general approach for global illumination of scenes
consisting of diffuse and pure specular surfaces. It is accurate be-
cause it can account for all possible light paths; and it is general
because it supports both the radiosity and ray tracing realms:
shapes bosh planar and curved materials both diffuse and spec-
ular, and lights both large and small. Distribution ray tracing
can be used to simulate effects not directly supported by the
algorithm.
Adaptive radiosity textures (rexes) are a new data struc-
ture that have several advantages over previous radiosity storage
schemes. They can adaptively subdivide themselves to resolve
sharp shadow edges to screen pixel size, thereby eliminating vis-
ible artifacts of radiosity sampling. Their subdivision can be
automatic, requiring no ad hoc user-selected parameters.
The current implementation is young, however, and many
problems remain. A terse fist follows: Good adaptive sampling
of area light sources appears to require a 4-D data structure. Bet-
ter methods are needed to determine the number of light rays.
The redistribution problems of histograms caused us to send each
light ray multiple times. To avoid this problem we could store
all (or selected) photon locations using kernel estimators [Sil-
verman86]. Excessive memory is currently devoted to the light
quadtree, since one node is stored per light ray. Perhaps the
quadtree could be subdivided in more-or-less scanline order, and
the memory recycled (quadtree restriction appears to complicate
this, however). Adaptive subdivision algorithms that compare
the ray trees of neighboring rays do not mix easily with path
tracing and distribution ray tracing, because the latter obscure
coherence. Last but not least, the interdependence of light ray
subdivision and rex subdivision is precarious.
Figure 12: Light focusing and reflection from a lens and chrome
ball. Scene is a glass lens formed by CSG intersection of two
spheres, a chrome ball, and a diffuse floor~ illuminated by a light
source off screen to the right. Note focusing of light through lens
onto floor at center (an LSSD path), reflection of refracted light
off ball onto floor (an LSS SD path involving both transmission
and reflection), the reflection of light off lens onto floor forming
a parabolic arc (an LSD path), and the reflection of the lens in
the ball (a LSSDSSE path, in full).
In spite of these challenges, we are hopeful. The approach
of bidirectional ray tracing using adaptive radiosity textures ap-
pears to contain the mechanisms needed to simulate global illu-
mination in a general way.
6 Acknowledgements
Thanks to Greg Ward for discussions about the global illumina-
tion problem, to Steve Omohundro for pointing me to the density
estimation literature, to Ken Turkowski and Apple Computer for
financial support, and to NSF grant CDA-8722788 for "Mam-
moth" time.
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