We have built a camera that can look around corners and beyond the line of sight. The camera uses light that travels from the object to the camera indirectly, by reflecting off walls or other obstacles, to reconstruct a 3D shape.
This document discusses compressive displays and related technologies for reducing the bandwidth requirements of multi-view and light field displays. It describes several technologies including layered 3D displays, polarization field displays, and high-rank 3D displays that decompose 4D light fields into lower dimensional representations. It also discusses using mathematical techniques like non-negative matrix factorization for further compressing display data. The document promotes open collaboration through the proposed Compressive Display Consortium to advance next generation displays.
Ramesh Raskar is an associate professor at the MIT Media Lab who researches computational photography. Some of his work includes using varying exposures in video to preserve high frequencies and combat motion blur. He has also developed techniques like image destabilization that use lens and sensor motion to programmably control defocus blur. Raskar aims to advance computational photography to enable high-level scene understanding through techniques like capturing depth from arrays of virtual cameras in LCD screens.
Though revolutionary in many ways, digital photography is essentially electronically implemented film photography. By contrast, computational photography exploits plentiful low-cost computing and memory, new kinds of digitally enabled sensors, optics, probes, smart lighting, and communication to capture information far beyond just a simple set of pixels. It promises a richer, even a multilayered, visual experience that may include depth, fused photo-video representations, or multispectral imagery. Professor Raskar will discuss and demonstrate advances he is working on in the areas of generalized optics, sensors, illumination methods, processing, and display, and describe how computational photography will enable us to create images that break from traditional constraints to retain more fully our fondest and most important memories, to keep personalized records of our lives, and to extend both the archival and the artistic possibilities of photography.
Compressed sensing allows for the recovery of sparse signals from fewer samples than required by the Nyquist rate. It works by finding the sparsest solution that is consistent with the observed samples. This is done using l1 norm optimization. The talk overviewed compressed sensing and provided several examples of applications that use it, such as single-pixel cameras, fast MRI, and light field photography. It concluded by discussing practical strategies for implementing compressed sensing using libraries like L1Magic.
The document discusses light field and coded aperture cameras. It describes the Stanford plenoptic camera which uses a microlens array to sample individual rays of light, capturing 14 pixels per lens. An alternative approach is a mask-based light field camera that uses a narrowband cosine mask to sample a coded combination of rays. This heterodyne approach captures half the brightness but avoids wasting pixels and issues with lens array alignment. The document outlines how such cameras can digitally refocus images and increase depth of field. It also discusses using the Fourier transform to compute a 4D light field from 2D photos captured with a mask.
The document discusses using coded masks and modulation techniques to capture light field information and enable digital refocusing and 6D displays with a single 2D sensor. It proposes placing a coded mask in front of the sensor to heterodyne the light field and extract its 4D information. Several applications are mentioned, including coded illumination for motion capture, a 6D display using spatial and illumination variation, and a light field camera that can digitally refocus using a single photograph.
1. Ramesh Raskar discusses his research in computational photography and creating new types of cameras that go beyond traditional camera capabilities.
2. The goal is to develop imaging platforms that have a deeper understanding of the visual world than humans by capturing and analyzing more information.
3. Examples of this research include cameras that can capture light fields and refocus images after capture, cameras that can remove motion blur in a single photo, and techniques for capturing high-speed motion with imperceptible tags.
We propose a flexible light field camera architecture that is at the convergence of optics, sensor electronics, and applied mathematics. Through the co-design of a sensor that comprises tailored, Angle Sensitive Pixels and advanced reconstruction algorithms, we show that—contrary to light field cameras today—our system can use the same measurements captured in a single sensor image to recover either a high-resolution 2D image, a low-resolution 4D light field using fast, linear processing, or a high-resolution light field using sparsity-constrained optimization.
This document discusses compressive displays and related technologies for reducing the bandwidth requirements of multi-view and light field displays. It describes several technologies including layered 3D displays, polarization field displays, and high-rank 3D displays that decompose 4D light fields into lower dimensional representations. It also discusses using mathematical techniques like non-negative matrix factorization for further compressing display data. The document promotes open collaboration through the proposed Compressive Display Consortium to advance next generation displays.
Ramesh Raskar is an associate professor at the MIT Media Lab who researches computational photography. Some of his work includes using varying exposures in video to preserve high frequencies and combat motion blur. He has also developed techniques like image destabilization that use lens and sensor motion to programmably control defocus blur. Raskar aims to advance computational photography to enable high-level scene understanding through techniques like capturing depth from arrays of virtual cameras in LCD screens.
Though revolutionary in many ways, digital photography is essentially electronically implemented film photography. By contrast, computational photography exploits plentiful low-cost computing and memory, new kinds of digitally enabled sensors, optics, probes, smart lighting, and communication to capture information far beyond just a simple set of pixels. It promises a richer, even a multilayered, visual experience that may include depth, fused photo-video representations, or multispectral imagery. Professor Raskar will discuss and demonstrate advances he is working on in the areas of generalized optics, sensors, illumination methods, processing, and display, and describe how computational photography will enable us to create images that break from traditional constraints to retain more fully our fondest and most important memories, to keep personalized records of our lives, and to extend both the archival and the artistic possibilities of photography.
Compressed sensing allows for the recovery of sparse signals from fewer samples than required by the Nyquist rate. It works by finding the sparsest solution that is consistent with the observed samples. This is done using l1 norm optimization. The talk overviewed compressed sensing and provided several examples of applications that use it, such as single-pixel cameras, fast MRI, and light field photography. It concluded by discussing practical strategies for implementing compressed sensing using libraries like L1Magic.
The document discusses light field and coded aperture cameras. It describes the Stanford plenoptic camera which uses a microlens array to sample individual rays of light, capturing 14 pixels per lens. An alternative approach is a mask-based light field camera that uses a narrowband cosine mask to sample a coded combination of rays. This heterodyne approach captures half the brightness but avoids wasting pixels and issues with lens array alignment. The document outlines how such cameras can digitally refocus images and increase depth of field. It also discusses using the Fourier transform to compute a 4D light field from 2D photos captured with a mask.
The document discusses using coded masks and modulation techniques to capture light field information and enable digital refocusing and 6D displays with a single 2D sensor. It proposes placing a coded mask in front of the sensor to heterodyne the light field and extract its 4D information. Several applications are mentioned, including coded illumination for motion capture, a 6D display using spatial and illumination variation, and a light field camera that can digitally refocus using a single photograph.
1. Ramesh Raskar discusses his research in computational photography and creating new types of cameras that go beyond traditional camera capabilities.
2. The goal is to develop imaging platforms that have a deeper understanding of the visual world than humans by capturing and analyzing more information.
3. Examples of this research include cameras that can capture light fields and refocus images after capture, cameras that can remove motion blur in a single photo, and techniques for capturing high-speed motion with imperceptible tags.
We propose a flexible light field camera architecture that is at the convergence of optics, sensor electronics, and applied mathematics. Through the co-design of a sensor that comprises tailored, Angle Sensitive Pixels and advanced reconstruction algorithms, we show that—contrary to light field cameras today—our system can use the same measurements captured in a single sensor image to recover either a high-resolution 2D image, a low-resolution 4D light field using fast, linear processing, or a high-resolution light field using sparsity-constrained optimization.
Computational Displays in 4D, 6D, 8D
We have explored how light propagates from thin elements into a volume for viewing for both automultiscopic displays and holograms. In particular, devices that are typically connected with geometric optics, like parallax barriers, differ in treatment from those that obey physical optics, like holograms. However, the two concepts are often used to achieve the same effect of capturing or displaying a combination of spatial and angular information. Our work connects the two approaches under a general framework based in ray space, from which insights into applications and limitations of both parallax-based and holography-based systems are observed.
Both parallax barrier systems and the practical holographic displays are limited in that they only provide horizontal parallax. Mathematically, this is equivalent to saying that they can always be expressed as a rank-1 matrix (i.e, a matrix in which all the columns are linearly related). Knowledge of this mathematical limitation has helped us to explore the space of possibilities and extend the capabilities of current display types. In particular, we have designed a display that uses two LCD panels, and an optimisation algorithm, to produce a content-adaptive automultiscopic display (SIGGRAPH Asia 2010).
(Joint work with R Horstmeyer, Se Baek Oh, George Barbastathis, Doug Lanman, Matt Hirsch and Yunhee Kim) http://cameraculture.media.mit.edu
In other work we have developed a 6D optical system that responds to changes in viewpoint as well as changes in surrounding light. Our lenticular array alignment allows us to achieve such a system as a passive setup, omitting the need for electrical components. Unlike traditional 2D flat displays, our 6D displays discretize the incident light field and modulate 2D patterns in order to produce super-realistic (2D) images. By casting light at variable intensities and angles onto our 6D displays, we can produce multiple images as well as store greater information capacity on a single 2D film (SIGGRAPH 2008).
Ramesh Raskar joined the Media Lab from Mitsubishi Electric Research Laboratories in 2008 as head of the Lab’s Camera Culture research group. His research interests span the fields of computational photography, inverse problems in imaging and human-computer interaction. Recent inventions include transient imaging to look around a corner, next generation CAT-Scan machine, imperceptible markers for motion capture (Prakash), long distance barcodes (Bokode), touch+hover 3D interaction displays (BiDi screen), low-cost eye care devices (Netra) and new theoretical models to augment light fields (ALF) to represent wave phenomena.
In 2004, Raskar received the TR100 Award from Technology Review, which recognizes top young innovators under the age of 35, and in 2003, the Global Indus Technovator Award, instituted at MIT to recognize the top 20 Indian technology innovators worldwide. In 2009, he was awarded a Sloan Research Fellowship. In 2010, he received the Darpa Young Faculty award. He holds over 40 US patents and has received four Mitsubishi Electric Invention Awards. He is currently co-authoring a book on Computational Photography. http://raskar.info
A compressive approach to light field synthesis with projection devices. We propose a novel, passive screen design that is combined with high-speed light field projection and nonnegative light field factorization. We demonstrate that the projector can alternatively achieve super-resolved and high dynamic range 2D image display when used with a conventional screen.
This document provides an introduction to light fields and their applications. It discusses the plenoptic function, which describes the set of all light rays that can be observed. Light fields can be parameterized in different ways, including using position and angle or using two planes. Applications of light fields include digital image refocusing, 3D displays, camera arrays, and controlling camera or object motion. Modern implementations include the Lytro light field camera, which uses a microlens array in front of the image sensor. Other applications discussed include using light fields to reduce lens glare and developing thin, depth-sensing LCD displays.
Ramesh Raskar discusses his research vision for computational photography and cameras of the future. He envisions cameras that can understand scenes at a higher level than humans by producing meaningful abstractions from vast amounts of visual data. His work includes techniques like looking around corners using transient imaging, long distance barcodes, light field displays, and augmented reality. The goal is to advance both imaging hardware and computational algorithms to create an "ultimate camera" beyond the limitations of traditional photography.
The document discusses computational photography and the future of cameras. It describes how cameras could encode light in time and space using coded apertures and flutter shutters to capture more information from a single photo. This would allow for features like digital refocusing and motion deblurring. It also discusses using masks inside cameras to capture 4D light field data with a 2D sensor, and how this could enable features like refocusing after the photo is taken. Finally, it proposes new types of cameras that could reconstruct 3D shape from a single photo or enable high-speed motion capture using imperceptible projected patterns.
The document discusses light field imaging principles and applications. It covers how light field cameras capture information about the direction of light rays in a scene to allow refocusing and changing perspectives in images. Applications discussed include virtual and augmented reality displays, as light field techniques can help reduce issues like vergence-accommodation conflict. It also describes research areas like improving light field storage and representation, capturing light fields with camera arrays, using microlens arrays in plenoptic cameras, and developing light field processing and rendering methods.
This document discusses light field photography. Light field photography captures information about the direction that light rays travel in a scene, allowing effects like image refocusing and new viewpoints to be generated. Traditionally, light field information has been captured using lenslet arrays or camera arrays. The proposed technology discussed is mask-coded light field projection, which uses a coded attenuation mask to project structured light and sample the light field of a scene with a single sensor. Potential applications mentioned include image refocusing, depth estimation, segmentation, object recognition, and changing viewpoints or enabling 3D displays.
Lytro Light Field Camera: from scientific research to a $50-million businessWeili Shi
Ren Ng improved light field camera technology during his doctoral research. This led to the founding of Lytro in 2006 to develop a consumer light field camera. Lytro launched its first camera in 2011, priced at $399, capturing full light field data while providing an easy user experience of refocusing photos after capture. The Lytro camera required its desktop software to interact with the proprietary light field data format and refocus images on a computer.
1. Ramesh Raskar is an associate professor at the MIT Media Lab researching computational photography.
2. Raskar discusses three levels of computational photography - epsilon, coded, and essence photography. Coded photography uses single or few snapshots but introduces reversible encoding of light through techniques like coded exposure and coded apertures.
3. Examples of coded photography techniques presented include flutter shutter motion deblurring, coded aperture defocus, optical heterodyning for lightfield or wavefront sensing, and using a coded glare mask. The goal is to create new imaging capabilities beyond what is possible with traditional cameras.
This document discusses spectral imaging techniques. It begins by describing the spectral data cube and how it can be obtained through spatial scanning with a 2D sensor or spectral scanning. It then covers various multiplexing techniques like image slicers that allow obtaining the spectral data cube instantaneously. Diffractive and computational imaging spectrometers are presented as ways to achieve snapshot spectral imaging. Applications discussed include white balancing, tracking, analyzing paintings, and satellite-based remote sensing.
The document discusses light field acquisition and the plenoptic function. It defines the plenoptic function as a 5D description of light rays as a function of position, direction, wavelength, and time. It describes how the plenoptic function can be parameterized and discusses several techniques for digitally capturing light fields, including camera arrays, parallax barriers, integral imaging with lenslets, and controlled camera motion. Applications mentioned include image-based rendering, digital refocusing, 3D displays, and spatial/temporal multiplexing.
This document summarizes Ramesh Raskar's work on coded computational photography. It describes using coded exposure to enable motion deblurring from a single photo in 2006. It also describes using a coded aperture to enable full resolution digital refocusing from a single photo in 2007 and using it for glare reduction in 2008. Additionally, it discusses using optical heterodyning to capture a 4D light field from a 2D sensor and single photo in 2007, as well as coding illumination and spectrum for applications like motion capture and acquiring an agile wavelength profile. The document outlines a progression from epsilon to coded to essence photography.
This document discusses techniques for creating accommodation-invariant near-eye displays. Current VR displays cause a vergence-accommodation conflict that produces eye fatigue. The authors investigate using point spread function engineering and multi-plane displays to remove the retinal blur cue and allow accommodation to match stereopsis. They describe a prototype that uses a spatial light modulator and focal sweep to render images with different depth-invariant point spread functions. A user study shows the prototype can drive accommodation with stereopsis alone. Future work includes improving image quality and investigating multifocal lenses and user comfort.
This document presents a method for adaptive color display using perceptually-driven factored spectral projection. It describes limitations of conventional displays in accurately reproducing colors due to their limited gamuts. The method formulates color reproduction as a nonlinear optimization problem to select multiple color primaries for each image, mapped to a display's gamut, in a way that minimizes perceptual errors in CIELAB color space. Evaluation shows the method significantly reduces color errors compared to legacy methods and allows displays to reproduce colors beyond their native gamut boundaries.
The document discusses image fusion and reconstruction techniques used in the CityBlock project, a precursor to Google Street View. It describes taking multiple photos of a scene with varied camera settings and then fusing the photos to merge the best parts from each image. This allows producing a composite image that captures details that would be missed in a single photo due to limitations of camera sensors and exposure settings. It also discusses using these techniques to reconstruct scenes by detecting changes between photos and computing scene invariants.
The document discusses using projectors to augment the real world by controlling light and projecting images onto surfaces. It describes capturing geometry and reflectance information of surfaces using cameras to allow projecting customized images. This could enable applications like annotating real objects or enhancing low-light videos with daytime context.
This document describes the concept of dual photography, which uses Helmholtz reciprocity to interchange lights and cameras in a scene. It discusses how the transposed transport matrix can be used to generate virtual captured images from virtual projected patterns. It also describes different methods used to capture the transport matrix, including fixed pattern scanning and adaptive multiplexed illumination. Limitations discussed include scenes with significant global illumination effects and situations where the camera and projector are at a large angle.
Millions of people worldwide need glasses or contact lenses to see or read properly. We introduce a computational display technology that predistorts the presented content for an observer, so that the target image is perceived without the need for eyewear. We demonstrate a low-cost prototype that can correct myopia, hyperopia, astigmatism, and even higher-order aberrations that are difficult to correct with glasses.
HIVE: holographic immersive virtual environments
MetaZtron Vision laser projector applications
Provides patent licensing information/ patent attorneys
Technology and Diane Troyer background.
MetaSphere hubs with Z*Rama screens and ZELF labs.
Z*Rama: Dome, Cinerama, Planetarium, Performance screens
ZELF: Zone Enhanced Location Fusion labs – HIVE applications.
Themed Edutainment: Location Based Entertainment
MetaStar: Philanthropic Model for sustainable community.
MetaSite: HIVE Community bottom up holodeck playpen turnkey
Innovation and Content tools for the local community.
Innovation and high end JOBS, JOBS, JOBS – new businesses.
STEAM TEAMS: Put A (art) into STEM –
New forms of immersive Edutainment and Health care.
Bottom up security and immersive first responder training
Communities thrive.
Tailored Displays to Compensate for Visual Aberrations - SIGGRAPH PresentationVitor Pamplona
Can we create a display that adapts itself to improve one's eyesight? Top figure compares the view of a 2.5-diopter farsighted individual in regular and tailored displays. We use currently available inexpensive technologies to warp light fields to compensate for refractive errors and scattering sites in the eye.
Raghuvardhan Kumar presented on femto photography. Femto photography can capture nearly one trillion frames per second using packets of photons. It works by illustrating objects using reflected photons. Some applications of femto photography include viewing molecular reactions and studying material properties. The technology offers advantages like capturing ultra-fast events but also has disadvantages such as requiring specialized equipment.
Computational Displays in 4D, 6D, 8D
We have explored how light propagates from thin elements into a volume for viewing for both automultiscopic displays and holograms. In particular, devices that are typically connected with geometric optics, like parallax barriers, differ in treatment from those that obey physical optics, like holograms. However, the two concepts are often used to achieve the same effect of capturing or displaying a combination of spatial and angular information. Our work connects the two approaches under a general framework based in ray space, from which insights into applications and limitations of both parallax-based and holography-based systems are observed.
Both parallax barrier systems and the practical holographic displays are limited in that they only provide horizontal parallax. Mathematically, this is equivalent to saying that they can always be expressed as a rank-1 matrix (i.e, a matrix in which all the columns are linearly related). Knowledge of this mathematical limitation has helped us to explore the space of possibilities and extend the capabilities of current display types. In particular, we have designed a display that uses two LCD panels, and an optimisation algorithm, to produce a content-adaptive automultiscopic display (SIGGRAPH Asia 2010).
(Joint work with R Horstmeyer, Se Baek Oh, George Barbastathis, Doug Lanman, Matt Hirsch and Yunhee Kim) http://cameraculture.media.mit.edu
In other work we have developed a 6D optical system that responds to changes in viewpoint as well as changes in surrounding light. Our lenticular array alignment allows us to achieve such a system as a passive setup, omitting the need for electrical components. Unlike traditional 2D flat displays, our 6D displays discretize the incident light field and modulate 2D patterns in order to produce super-realistic (2D) images. By casting light at variable intensities and angles onto our 6D displays, we can produce multiple images as well as store greater information capacity on a single 2D film (SIGGRAPH 2008).
Ramesh Raskar joined the Media Lab from Mitsubishi Electric Research Laboratories in 2008 as head of the Lab’s Camera Culture research group. His research interests span the fields of computational photography, inverse problems in imaging and human-computer interaction. Recent inventions include transient imaging to look around a corner, next generation CAT-Scan machine, imperceptible markers for motion capture (Prakash), long distance barcodes (Bokode), touch+hover 3D interaction displays (BiDi screen), low-cost eye care devices (Netra) and new theoretical models to augment light fields (ALF) to represent wave phenomena.
In 2004, Raskar received the TR100 Award from Technology Review, which recognizes top young innovators under the age of 35, and in 2003, the Global Indus Technovator Award, instituted at MIT to recognize the top 20 Indian technology innovators worldwide. In 2009, he was awarded a Sloan Research Fellowship. In 2010, he received the Darpa Young Faculty award. He holds over 40 US patents and has received four Mitsubishi Electric Invention Awards. He is currently co-authoring a book on Computational Photography. http://raskar.info
A compressive approach to light field synthesis with projection devices. We propose a novel, passive screen design that is combined with high-speed light field projection and nonnegative light field factorization. We demonstrate that the projector can alternatively achieve super-resolved and high dynamic range 2D image display when used with a conventional screen.
This document provides an introduction to light fields and their applications. It discusses the plenoptic function, which describes the set of all light rays that can be observed. Light fields can be parameterized in different ways, including using position and angle or using two planes. Applications of light fields include digital image refocusing, 3D displays, camera arrays, and controlling camera or object motion. Modern implementations include the Lytro light field camera, which uses a microlens array in front of the image sensor. Other applications discussed include using light fields to reduce lens glare and developing thin, depth-sensing LCD displays.
Ramesh Raskar discusses his research vision for computational photography and cameras of the future. He envisions cameras that can understand scenes at a higher level than humans by producing meaningful abstractions from vast amounts of visual data. His work includes techniques like looking around corners using transient imaging, long distance barcodes, light field displays, and augmented reality. The goal is to advance both imaging hardware and computational algorithms to create an "ultimate camera" beyond the limitations of traditional photography.
The document discusses computational photography and the future of cameras. It describes how cameras could encode light in time and space using coded apertures and flutter shutters to capture more information from a single photo. This would allow for features like digital refocusing and motion deblurring. It also discusses using masks inside cameras to capture 4D light field data with a 2D sensor, and how this could enable features like refocusing after the photo is taken. Finally, it proposes new types of cameras that could reconstruct 3D shape from a single photo or enable high-speed motion capture using imperceptible projected patterns.
The document discusses light field imaging principles and applications. It covers how light field cameras capture information about the direction of light rays in a scene to allow refocusing and changing perspectives in images. Applications discussed include virtual and augmented reality displays, as light field techniques can help reduce issues like vergence-accommodation conflict. It also describes research areas like improving light field storage and representation, capturing light fields with camera arrays, using microlens arrays in plenoptic cameras, and developing light field processing and rendering methods.
This document discusses light field photography. Light field photography captures information about the direction that light rays travel in a scene, allowing effects like image refocusing and new viewpoints to be generated. Traditionally, light field information has been captured using lenslet arrays or camera arrays. The proposed technology discussed is mask-coded light field projection, which uses a coded attenuation mask to project structured light and sample the light field of a scene with a single sensor. Potential applications mentioned include image refocusing, depth estimation, segmentation, object recognition, and changing viewpoints or enabling 3D displays.
Lytro Light Field Camera: from scientific research to a $50-million businessWeili Shi
Ren Ng improved light field camera technology during his doctoral research. This led to the founding of Lytro in 2006 to develop a consumer light field camera. Lytro launched its first camera in 2011, priced at $399, capturing full light field data while providing an easy user experience of refocusing photos after capture. The Lytro camera required its desktop software to interact with the proprietary light field data format and refocus images on a computer.
1. Ramesh Raskar is an associate professor at the MIT Media Lab researching computational photography.
2. Raskar discusses three levels of computational photography - epsilon, coded, and essence photography. Coded photography uses single or few snapshots but introduces reversible encoding of light through techniques like coded exposure and coded apertures.
3. Examples of coded photography techniques presented include flutter shutter motion deblurring, coded aperture defocus, optical heterodyning for lightfield or wavefront sensing, and using a coded glare mask. The goal is to create new imaging capabilities beyond what is possible with traditional cameras.
This document discusses spectral imaging techniques. It begins by describing the spectral data cube and how it can be obtained through spatial scanning with a 2D sensor or spectral scanning. It then covers various multiplexing techniques like image slicers that allow obtaining the spectral data cube instantaneously. Diffractive and computational imaging spectrometers are presented as ways to achieve snapshot spectral imaging. Applications discussed include white balancing, tracking, analyzing paintings, and satellite-based remote sensing.
The document discusses light field acquisition and the plenoptic function. It defines the plenoptic function as a 5D description of light rays as a function of position, direction, wavelength, and time. It describes how the plenoptic function can be parameterized and discusses several techniques for digitally capturing light fields, including camera arrays, parallax barriers, integral imaging with lenslets, and controlled camera motion. Applications mentioned include image-based rendering, digital refocusing, 3D displays, and spatial/temporal multiplexing.
This document summarizes Ramesh Raskar's work on coded computational photography. It describes using coded exposure to enable motion deblurring from a single photo in 2006. It also describes using a coded aperture to enable full resolution digital refocusing from a single photo in 2007 and using it for glare reduction in 2008. Additionally, it discusses using optical heterodyning to capture a 4D light field from a 2D sensor and single photo in 2007, as well as coding illumination and spectrum for applications like motion capture and acquiring an agile wavelength profile. The document outlines a progression from epsilon to coded to essence photography.
This document discusses techniques for creating accommodation-invariant near-eye displays. Current VR displays cause a vergence-accommodation conflict that produces eye fatigue. The authors investigate using point spread function engineering and multi-plane displays to remove the retinal blur cue and allow accommodation to match stereopsis. They describe a prototype that uses a spatial light modulator and focal sweep to render images with different depth-invariant point spread functions. A user study shows the prototype can drive accommodation with stereopsis alone. Future work includes improving image quality and investigating multifocal lenses and user comfort.
This document presents a method for adaptive color display using perceptually-driven factored spectral projection. It describes limitations of conventional displays in accurately reproducing colors due to their limited gamuts. The method formulates color reproduction as a nonlinear optimization problem to select multiple color primaries for each image, mapped to a display's gamut, in a way that minimizes perceptual errors in CIELAB color space. Evaluation shows the method significantly reduces color errors compared to legacy methods and allows displays to reproduce colors beyond their native gamut boundaries.
The document discusses image fusion and reconstruction techniques used in the CityBlock project, a precursor to Google Street View. It describes taking multiple photos of a scene with varied camera settings and then fusing the photos to merge the best parts from each image. This allows producing a composite image that captures details that would be missed in a single photo due to limitations of camera sensors and exposure settings. It also discusses using these techniques to reconstruct scenes by detecting changes between photos and computing scene invariants.
The document discusses using projectors to augment the real world by controlling light and projecting images onto surfaces. It describes capturing geometry and reflectance information of surfaces using cameras to allow projecting customized images. This could enable applications like annotating real objects or enhancing low-light videos with daytime context.
This document describes the concept of dual photography, which uses Helmholtz reciprocity to interchange lights and cameras in a scene. It discusses how the transposed transport matrix can be used to generate virtual captured images from virtual projected patterns. It also describes different methods used to capture the transport matrix, including fixed pattern scanning and adaptive multiplexed illumination. Limitations discussed include scenes with significant global illumination effects and situations where the camera and projector are at a large angle.
Millions of people worldwide need glasses or contact lenses to see or read properly. We introduce a computational display technology that predistorts the presented content for an observer, so that the target image is perceived without the need for eyewear. We demonstrate a low-cost prototype that can correct myopia, hyperopia, astigmatism, and even higher-order aberrations that are difficult to correct with glasses.
HIVE: holographic immersive virtual environments
MetaZtron Vision laser projector applications
Provides patent licensing information/ patent attorneys
Technology and Diane Troyer background.
MetaSphere hubs with Z*Rama screens and ZELF labs.
Z*Rama: Dome, Cinerama, Planetarium, Performance screens
ZELF: Zone Enhanced Location Fusion labs – HIVE applications.
Themed Edutainment: Location Based Entertainment
MetaStar: Philanthropic Model for sustainable community.
MetaSite: HIVE Community bottom up holodeck playpen turnkey
Innovation and Content tools for the local community.
Innovation and high end JOBS, JOBS, JOBS – new businesses.
STEAM TEAMS: Put A (art) into STEM –
New forms of immersive Edutainment and Health care.
Bottom up security and immersive first responder training
Communities thrive.
Tailored Displays to Compensate for Visual Aberrations - SIGGRAPH PresentationVitor Pamplona
Can we create a display that adapts itself to improve one's eyesight? Top figure compares the view of a 2.5-diopter farsighted individual in regular and tailored displays. We use currently available inexpensive technologies to warp light fields to compensate for refractive errors and scattering sites in the eye.
Raghuvardhan Kumar presented on femto photography. Femto photography can capture nearly one trillion frames per second using packets of photons. It works by illustrating objects using reflected photons. Some applications of femto photography include viewing molecular reactions and studying material properties. The technology offers advantages like capturing ultra-fast events but also has disadvantages such as requiring specialized equipment.
Ramesh Raskar is an associate professor at the MIT Media Lab who is working on femto-photography, which involves capturing light and motion at extremely high speeds of trillion frames per second. Some applications of this technology include seeing around corners by analyzing light that bounces off surfaces, using computational photography techniques to avoid collisions, and developing new medical imaging techniques. Raskar's work aims to advance computational photography and capture light and motion at speeds much faster than conventional cameras.
This document discusses femto-photography, a technique developed by Ramesh Raskar at MIT Media Lab that uses ultrafast cameras to capture photons reflected off surfaces and around corners. It works by analyzing the paths of multiple photons reflected from an object to reconstruct what is around the corner. The document explains that streak cameras are used which can capture images at trillionths of a second, and describes potential applications in collision avoidance, medical imaging, and seeing motion beyond line of sight.
The seemingly impossible task of recording what is beyond the line of sight is possible due to ultra‐fast imaging. A new form of photography, Femto-photography exploits the finite speed of light and analyzes 'echoes of light'.
Femto-photography consists of femtosecond laser illumination, picosecond-accurate detectors and mathematical inversion techniques. By emitting short laser pulses and analyzing multi-bounce reflections we can estimate hidden geometry. In transient light transport, we account for the fact that speed of light is finite. Light travels ~1 foot/nanosecond and by sampling the light at pico-second resolution, we can estimate shapes with centimeter accuracy.
Potential applications include search and rescue planning in hazardous conditions, collision avoidance for cars, and robots in industrial environments. Transient imaging also has significant potential benefits in medical imaging that could allow endoscopes to view around obstacles inside the human body.
Temporal Frequency Probing for 5D Transient Analysis of Global Light TransportMatthew O'Toole
This document proposes a new approach called temporal frequency probing to analyze light transport using time-of-flight (ToF) cameras and projectors. By projecting patterns at different modulation frequencies and capturing the returning light with a ToF camera, it can separate direct from indirect light transport and further separate caustic from diffuse indirect light. This allows it to reconstruct high temporal resolution "light-in-flight" videos depicting the propagation of light over time within a scene. The approach leverages decades of research on light transport analysis and provides a new paradigm for studying transient 5D light transport using commercially available ToF sensors and projectors.
This document describes a Packet Tracer activity where students will configure and test web and email services on simulated servers. The activity involves two parts: 1) configuring and verifying web services on CentralServer and BranchServer, and 2) configuring and verifying email services to send and receive email on the servers. Students will configure clients to access the web and email services and send emails between clients to verify connectivity.
This document summarizes the work of Ramesh Raskar and his lab at the MIT Media Lab on camera culture and computational imaging. Some of the key areas of research include developing eyeglasses-free displays, smartphone cameras for health screening and spectroscopy, and using computer vision and crowdsourcing to evaluate cities. The document also lists several projects involving using light in new ways like seeing around corners, identifying materials from a single viewpoint, and developing high speed cameras with attosecond resolution to capture light-matter interactions.
This document describes a multi-camera time-of-flight imaging system that uses multiple synchronized cameras and light sources. It allows control over modulation signals to capture dynamic scenes and extract depth, velocity and non-line-of-sight motion information. The system architecture uses a direct digital synthesis chip to generate programmable modulation signals, synchronized signal conditioning circuits and a real-time controller to coordinate image capture across multiple time-of-flight cameras. It aims to enable applications like phased array imaging, simultaneous Doppler velocity capture and detecting motion behind scattering media.
This document provides tips for creating effective PowerPoint presentations. It notes that many presentations are "unbearable" due to a lack of significance, structure, simplicity, and rehearsal. It emphasizes the importance of having a clear purpose for your presentation, using a simple structure like problem-solution, keeping slides concise with minimal text and images over clipart, writing speaker notes instead of long slides for printing, and rehearsing your presentation aloud to work out any issues. The overall message is that presentations should be passionate, memorable and scalable through a focus on simplicity and clarity of message.
This document proposes a laser tether method for ultra-precise formation flight using photon thrusters and tethers. It would use the counterbalancing forces of tether tension and photon thrust produced via intracavity laser arrangements to maintain inter-spacecraft distances to the nanometer level over tens of kilometers. The system aims to enable propellant-free and contamination-free long-term precise formation flying for applications such as space telescopes and interferometry missions. It analyzes the technology readiness of components and outlines a development roadmap.
SIGGRAPH 2018 - Full Rays Ahead! From Raster to Real-Time RaytracingElectronic Arts / DICE
In this presentation part of the "Introduction to DirectX Raytracing" course, Colin Barré-Brisebois of SEED discusses some of the challenges the team had to go through when going from raster to real-time raytracing for Project PICA PICA.
Accelarating Optical Quadrature Microscopy Using GPUsPerhaad Mistry
1) Phase unwrapping is used in optical quadrature microscopy to determine viability of embryos by counting cells after unwrapping. It needs to be done at near real-time speeds to analyze sample changes.
2) The paper implements minimum LP norm phase unwrapping and affine transformations on a GPU to improve performance and latency for optical microscopy research.
3) Performance results show a 5.24x speedup for total phase unwrapping time compared to a serial CPU implementation. Further optimizations like multi-GPU support could improve speeds for higher image acquisition rates.
Motion capture technology involves recording human movement through specialized cameras and mapping it onto digital character models. Historically, rotoscoping was used, which involved animators tracing live-action footage frame-by-frame. Now, motion capture uses optical, magnetic, or mechanical techniques to track markers on an actor's body in real-time. The captured motion data is then fitted to a digital skeleton and can be edited or processed before being applied to animations. Motion capture has applications in entertainment, medicine, education, science, engineering, and more.
Keywords: Signal processing, Applied optics, Computer graphics and vision, Electronics, Art, and Online photo collections
A computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. We will discuss and play with thermal cameras, multi-spectral cameras, high-speed, and 3D range-sensing cameras and camera arrays. We will learn about opportunities in scientific and medical imaging, mobile-phone based photography, camera for HCI and sensors mimicking animal eyes.
We will learn about the complete camera pipeline. In several hands-on projects we will build several physical imaging prototypes and understand how each stage of the imaging process can be manipulated.
We will learn about modern methods for capturing and sharing visual information. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded -- beyond those present in traditional protographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aesthetic renderings of the visual information can be synthesized.
In this couse we will study this emerging multi-disciplinary field -- one which is at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. We will examine whether such innovative camera-like sensors can overcome the tough problems in scene understanding and generate insightful awareness. In addition, we will develop new algorithms to exploit unusual optics, programmable wavelength control, and femto-second accurate photon counting to decompose the sensed values into perceptually critical elements.
Localization of Objects Using Cross-Correlation of Shadow Fading Noise and Co...Rana Basheer
When a radio transmitter is mobile, obstacles in the
radio path can cause temporal variation in Received Signal Strength Indicator (RSSI) measured by receivers due to multipath and shadow fading. While fading, in general, is detrimental to accurately localizing a target, fading correlation between adjacent receivers may be exploited to improve localization accuracy. However, multipath fading correlation is a short range phenomenon that rapidly falls to zero within a wavelength whereas,
shadow fading correlation is independent of signal wavelength and has longer range thereby making it suitable for localization with wireless transceivers that operate at shorter wavelength. Therefore,
this paper presents a novel wireless localization scheme that employs a combination of cross-correlation between shadow fading noise and copula technique to recursively estimate the location of a transmitter. A stochastic filter that models multipath fading as an Ornstein-Uhlenbeck process followed by a Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) filtering is
proposed to extract shadow fading residuals from measured RSSI values. Subsequently, Student-T Copula function is used to create the log likelihood function, which acts as the cost function for localization, by combining spatial shadow fading correlation arising among adjacent receivers due to pedestrian traffic in the area. Maximum Likelihood Estimate (MLE) is used for position estimation as it inherits the statistical consistency and asymptotic
normality. The performance of our proposed localization method is validated over simulations and hardware experiments.
SIGGRAPH 2014 Course on Computational Cameras and Displays (part 4)Matthew O'Toole
Recent advances in both computational photography and displays have given rise to a new generation of computational devices. Computational cameras and displays provide a visual experience that goes beyond the capabilities of traditional systems by adding computational power to optics, lights, and sensors. These devices are breaking new ground in the consumer market, including lightfield cameras that redefine our understanding of pictures (Lytro), displays for visualizing 3D/4D content without special eyewear (Nintendo 3DS), motion-sensing devices that use light coded in space or time to detect motion and position (Kinect, Leap Motion), and a movement toward ubiquitous computing with wearable cameras and displays (Google Glass).
This short (1.5 hour) course serves as an introduction to the key ideas and an overview of the latest work in computational cameras, displays, and light transport.
1) The document presents a new method for automatically registering synthetic aperture radar (SAR) imagery to light detection and ranging (LIDAR) data and optical images using digital elevation models (DEMs).
2) The method works by generating a predicted SAR image from the DEM and sensor model, registering this predicted image to the actual SAR image, and refining the sensor model.
3) The results show accurate registration of SAR imagery to LIDAR DEMs and multispectral imagery, with registration errors of 1-2 meters.
This document describes a method for automatically registering synthetic aperture radar (SAR) imagery to light detection and ranging (LIDAR) data and optical images. The method uses a high-resolution digital elevation model (DEM) derived from LIDAR or other sources to generate a predicted SAR image. It then registers the predicted and actual SAR images to refine the sensor model. The same approach can register SAR and optical sensors by using the DEM as a bridge. The method was tested on SAR-LIDAR registration of a COSMO-SkyMed SAR image to a BuckEye LIDAR DEM, achieving a registration accuracy of 1-2 meters. It was also used for SAR-MSI registration and a three-
If you are inspired by an idea 'X', how will you come up with the neXt idea? This presentation shows 6 different ways you can exercise your mind in an attempt to develop the next cool idea.
http://raskar.info
http://cameraculture.info
The document provides details about the research background and interests of researcher Fang Can. It outlines his educational background in electrical engineering and computer science. It also describes his technical skills in mathematics, optimization, algorithm development, and optics. The document discusses Fang's PhD research projects which took graph-theoretic and geometric approaches to problems in communication networks and wireless sensor networks. It provides examples of his current work developing multi-spectral optical probes and a spectrum-scanning microscope to analyze tissue and cell samples.
Eng remote sensing and image measurementWataru Ohira
Remote sensing uses sensors on platforms like satellites or aircraft to collect imagery and geospatial data of the Earth. Various sensors can extract different types of information like color, geometry, or 3D coordinates using principles like stereo imagery. Mathematical models like collinearity equations relate image coordinates to ground coordinates. Sensor position and attitude can be estimated using ground control points. 3D measurements are possible with stereo imagery. Different sensor types exist for applications like vegetation monitoring, land use mapping, and disaster monitoring.
SAL3D presentation - AQSENSE's 3D machine vision libraryAQSENSE S.L.
The 3D Shape Analysis Library (http://www.aqsense.com/products/sal3d) is the first hardware independent software architecture for range map and poing cloud processing, fully oriented to laser triangulation and 3D machine vision applications.
SAL3D means speed, accuracy, and reliability to machine builders, equipment manufacturers, system integrators, and volume end users demanding maximum flexibility and customization in their vision systems. Tools can be integrated as DLL's that allow developers access to third party components usable side by side with SAL's tools resulting in rapid development of highly complex processing tasks.
This document discusses the development of a high-speed single-photon camera. It motivates the need for cameras with both extreme sensitivity and high speeds to enable applications like fluorescence correlation spectroscopy (FCS). The camera uses an array of single-photon avalanche diode (SPAD) detectors integrated on a CMOS chip. Each pixel contains circuitry to independently count and time photons with microsecond resolution at frame rates over 100,000 frames per second. The camera has been used for applications demonstrating sub-Rayleigh imaging and high-throughput FCS.
WE3.L10.3: THE FUTURE OF SPACEBORNE SYNTHETIC APERTURE RADARgrssieee
The document discusses the history and future of spaceborne synthetic aperture radar (SAR). It summarizes key details of early SAR satellites like Seasat and missions since 1978. The text outlines future requirements like wider coverage, higher resolution, and new data products. It proposes concepts like bistatic SAR, polarimetric SAR interferometry, and 4D SAR tomography to measure changes in vegetation, ice, and other surfaces over time. Finally, it discusses ideas proposed by Kiyo Tomiyasu for compact antennas and GEO-LEO SAR configurations to enable more frequent global monitoring with high resolution.
2008 brokerage 03 scalable 3 d models [compatibility mode]imec.archive
1) There is a trend towards capturing and modeling massive 3D environments and dynamic 4D scenes for applications like virtual worlds, games, and navigation systems.
2) Acquiring and processing large amounts of 3D data poses challenges for technologies related to acquisition, editing, transmission, rendering and presentation as the scale increases.
3) The document discusses various methods for large-scale 3D acquisition including structure from motion, stereo vision, LIDAR, structured light scanning, as well as challenges in editing, streaming, and rendering massive 3D models.
This document discusses methods for large-scale image annotation and categorization using weakly supervised training data. It describes how traditional methods do not scale well to large datasets. Recent methods exploit linear models and distance metric learning to better scale. Specifically, Canonical Contextual Distance learning finds linear transformations to maximize correlation between image and label features in a latent subspace, providing a probabilistic similarity measure. This allows image auto-annotation on large datasets.
This document summarizes a class on acceleration structures for ray tracing. It discusses building bounding volume hierarchies and using them to accelerate ray intersection tests. Uniform grids, kd-trees, and binary space partitioning trees are covered as approaches for spatial subdivision. The role of acceleration structures in speeding up global illumination calculations is also discussed.
Similar to CORNAR: Looking Around Corners using Trillion FPS Imaging (20)
ACM SIGGRAPH is delighted to present the 2017 Computer Graphics Achievement Award to Ramesh Raskar in recognition of his pioneering contributions to the fields of computational photography and light transport and for applying these technologies for social impact.
https://www.siggraph.org/about/awards/2017-cg-achievement-award-ramesh-raskar/
I recently gave a talk at ICCP 2015 and clarified that we should stop working on coded aperture for focus effects! (Thus negating my team's work in this area.). I also spoke about the lost decade of computational photography and how we have wasted too many years working on the wrong problems.
The way back to normal starts here
We all want to get out of the house. To reopen the economy. To feel secure again. Safe Paths builds tools that help communities flatten the curve of COVID-19 — together. CovidSafePaths.org
This document discusses privacy-aware artificial intelligence and techniques like split learning and federated learning. It notes the tension between utility and privacy with AI systems and proposes approaches like differential privacy, homomorphic encryption, and sharing wisdom rather than raw data to develop private AI. Split learning and federated learning allow models to be trained from distributed data sources without aggregating private information. The goal is to capture precise data to learn and act while respecting privacy through techniques that train models from decentralized and anonymized data.
Video: https://www.youtube.com/watch?v=2jq_5FaQbTg
After different rejections, the project of a lifetime Ramesh Raskar (associate professor at MIT) finally comes to life.
How did he manage to get his way out of this jungle of misleading signs and career traps? By becoming a pathfinder: always tense towards your goal but also critical and ready to adjust his strategy to reach it.
An incredible life lesson that he gave us in this talk at the last FAIL at Massachusetts Institute of Technology (MIT).
https://www.youtube.com/watch?v=2jq_5FaQbTg&feature=youtu.be&fbclid=IwAR3aAo7SIiCuHY_6ICTjXLOpNBUBwEEJUq72pD-V8N2nX2cWaVIxtPM1gBM
Ramesh Raskar is an Associate Professor at MIT Media Lab and directs the Camera Culture research group. His focus is on AI and Imaging for health and sustainability. These interfaces span research in physical (e.g., sensors, health-tech), digital (e.g., automating machine learning) and global (e.g., geomaps, autonomous mobility) domains. He received the Lemelson Award (2016), ACM SIGGRAPH Achievement Award (2017), DARPA Young Faculty Award (2009), Alfred P. Sloan Research Fellowship (2009), TR100 Award from MIT Technology Review (2004) and Global Indus Technovator Award (2003). He has worked on special research projects at Google [X] and Facebook and co-founded/advised several companies.
http://raskar.info or CameraCulture Wiki Page
How to come up w ideas: Idea Hexagon
How to write a paper
How to give a talk
Open research problems
How to decide merit of a project
How to attend a conference, brainstorm
Strive for Five
Before 5 teams
Be early, let others do details
Beyond 5 years
What no one is thinking about
Within 5 steps of Human Impact
Relevance
Beyond 5 mins of instruction
Deep, iterative, participatory
Fusing 5+ Expertise
Fun, barrier for others
Associate Professor, MIT Media Lab
Ramesh Raskar is founder of the Camera Culture research group at the Massachusetts Institute of Technology (MIT) Media Lab and associate professor of Media Arts and Sciences at MIT. Raskar is the co-inventor of radical imaging solutions including femto-photography, an ultra-fast imaging camera that can see around corners, low-cost eye-care solutions for the developing world and a camera that allows users to read pages of a book without opening the cover. He is a pioneer in the fields of imaging, computer vision and machine learning.
Raskar’s focus is on building interfaces between social systems and cyber-physical systems. These interfaces span research in physical (e.g., sensors, health-tech), digital (e.g., tools to enable keeping data private in distributed machine learning applications) and global (e.g., geomaps, autonomous mobility) domains. Recent inventions by Raskar’s team include transient imaging to look around a corner, a next-generation CAT-scan machine, imperceptible markers for motion capture, long-distance barcodes, touch + hover 3D interaction displays and new theoretical models to augment light fields to represent wave phenomena.
Raskar has dedicated his career to linking the best of the academic and entrepreneurial worlds with young engineers, igniting a passion for impact inventing. Raskar seeks to catalyze change on a massive scale by launching platforms that empower inventors to create solutions to improve lives globally.
Raskar has received the Lemelson Award, ACM SIGGRAPH Achievement Award, DARPA Young Faculty Award, Alfred P. Sloan Research Fellowship, TR100 Award from MIT Technology Review and Global Indus Technovator Award. He has worked on special research projects at Google [X] and Facebook and co-founded and advised several companies. He holds more than 80 US patents.
Making the Invisible Visible: Within Our Bodies, the World Around Us, and Beyond
1. Ramesh Raskar discusses using AI, sensors, and interactive technology to augment surgeons by creating a "Waze for surgeons" that allows sharing tips, rapid training, and detecting anomalies.
2. He proposes capturing millions of surgery videos to analyze with AI and create a library of complications.
3. The goal is to guide surgeons with augmented reality, haptics, and screens to improve precision health for individual patients and population health across surgical patients.
We need to transition from analysis to synthesis when it comes to large scale image based studies of satellite or street level images.
Large scale, image based studies have the ability to unlock the human potential and really address some of the most important societal problems. The question really is, are we going to do that through analysis or are we going to step up to the game and actually start doing synthesis? Are we only go to study and observations or are we going to go and actually make an impact in the society?
Can global image repositories help UN's sustainable development goals (SDGs)? help us understand the social determinants of health? Satellite imagery, Google street view and user contributed photos from a global image repository are being used for large scale image-based studies, visual census and sentiment analysis [Ermon][http://StreetScore.media.mit.edu]. But we need to go beyond simply relying on big data for investigating social questions via remote analysis. We need to transition from analysis to synthesis. For deployable social solutions, we need to consider the full stack of physical devices, organizational interests and sector-specific resources.
Image-based large studies allow us to predict poverty from daytime and nighttime satellite imagery which can influence critical decisions for aid and development planning. In project ‘StreetScore’, our group has shown that semantic analysis of street level imagery such as Google Streetview, can provide varied insights rich in urban perception; our recent project ‘StreetChange’ shows the benefits of time-series data in driving these insights (http://streetchange.media.mit.edu).
We have seen some amazing work and you'll hear from Stephano about poverty mapping my glove previous collaborators to a population density crop maps, Betaine. So we had been, that's been fantastic progress in, in using a global industry, uh, in, in these areas that are taken from satellites or drones and then a street level imagery is also very widely available, either very structured like Google street view, but also from a user contributor photos and to that Nikki like and others in my group have been working on can we do a sentiment analysis of, of this imagery in this case, sentiment analysis of the perceived safety just for Google Street and main street and then create kind of citywide maps of a perceived safety that can be used by city planners and urban planners. So, which is great. But coming back to analysis versus synthesis opportunities, I'm going to give you a flavor of one of the projects we worked on a which is street addresses.
Project page: https://splitlearning.github.io/
Papers: https://arxiv.org/search/cs?searchtype=author&query=Raskar
Video: https://www.youtube.com/watch?v=8GtJ1bWHZvg
Split learning for health: Distributed deep learning without sharing raw patient data: https://arxiv.org/pdf/1812.00564.pdf
Distributed learning of deep neural network over multiple agents
https://www.sciencedirect.com/science/article/pii/S1084804518301590
Otkrist Gupta, Ramesh Raskar,
In domains such as health care and finance, shortage of labeled data and computational resources is a critical issue while developing machine learning algorithms. To address the issue of labeled data scarcity in training and deployment of neural network-based systems, we propose a new technique to train deep neural networks over several data sources. Our method allows for deep neural networks to be trained using data from multiple entities in a distributed fashion. We evaluate our algorithm on existing datasets and show that it obtains performance which is similar to a regular neural network trained on a single machine. We further extend it to incorporate semi-supervised learning when training with few labeled samples, and analyze any security concerns that may arise. Our algorithm paves the way for distributed training of deep neural networks in data sensitive applications when raw data may not be shared directly.
What is SIGGRAPH NEXT?
By Juliet Fiss
What will be the next big thing at SIGGRAPH, and how can the SIGGRAPH community contribute in an impactful way to fields outside of traditional computer graphics? SIGGRAPH NEXT at SIGGRAPH 2015 explored these questions. In this new addition to the SIGGRAPH program, an eclectic set of speakers gave TED-style talks and posed grand challenges to the SIGGRAPH community. In this blog post, Professor Ramesh Raskar of the MIT Media Lab introduces SIGGRAPH NEXT and outlines his vision for it.
What will be the next big thing at SIGGRAPH?
The SIGGRAPH community has a set of hammers that it uses to solve problems: geometry processing, rendering, animation, and imaging. What will be the next hammer, the next major field of study, appear at SIGGRAPH? Let’s examine where our research ideas come from. Often, advances in machine learning, optimization, signal processing, and optics forge our hammers. Our selection of hammer also depends on the nails we see. The most common application areas of computer graphics currently include computer-aided design, movies, games, and photography.
We often ask: “Does this work contribute to SIGGRAPH techniques?”
We should also ask, “Does this work contribute SIGGRAPH techniques to _____?”
When we answer the challenges posed by these traditional application areas of computer graphics, we are “drinking our own champagne.” We have made amazing progress in these application areas, and we should celebrate! SIGGRAPH NEXT is about finding new varieties of champagne; for that, we need new varieties of grapes. We should invite others from nontraditional and emerging application areas to enjoy our champagne with us, and they will become part of our community. First, we can expand our work in existing areas like mobile, user interaction, virtual reality, fabrication, and new types of cameras. We can also expand into emerging areas such as healthcare, energy, education, entrepreneurship, materials, tissue fabrication, and social media. What’s next?
Professor Raskar highlights three top areas where we can make an impact. One big take-home message is that many of these applications involve biology: bio is the new digital, and it will affect us ubiquitously.
'Media' is a plural for medium. The medium for impact of digital technologies at MIT Media Lab can be photons, electrons, neurons, atoms, cells, musical notes and more.
Over the last 40 years, computing has moved from processor, network, social and more sensory.
MIT Media Lab works at the intersection of computing and such media for human-centric technologies.
Ramesh Raskar
MIT Media Lab
Ramesh Raskar is an Associate Professor at MIT Media Lab. Ramesh Raskar joined the Media Lab from Mitsubishi Electric Research Laboratories in 2008 as head of the Lab’s Camera Culture research group. His research interests span the fields of computational photography, inverse problems in imaging and human-computer interaction. Recent projects and inventions include transient imaging to look around a corner, a next generation CAT-Scan machine, imperceptible markers for motion capture (Prakash), long distance barcodes (Bokode), touch+hover 3D interaction displays (BiDi screen), low-cost eye care devices (Netra,Catra), new theoretical models to augment light fields (ALF) to represent wave phenomena and algebraic rank constraints for 3D displays(HR3D).
In 2004, Raskar received the TR100 Award from Technology Review, which recognizes top young innovators under the age of 35, and in 2003, the Global Indus Technovator Award, instituted at MIT to recognize the top 20 Indian technology innovators worldwide. In 2009, he was awarded a Sloan Research Fellowship. In 2010, he received the Darpa Young Faculty award. Other awards include Marr Prize honorable mention 2009, LAUNCH Health Innovation Award, presented by NASA, USAID, US State Dept and NIKE, 2010, Vodafone Wireless Innovation Project Award (first place), 2011. He holds over 50 US patents and has received four Mitsubishi Electric Invention Awards. He is currently co-authoring a book on Computational Photography.
This document provides an overview of the pipeline for multiview computer vision. It describes taking multiple photographs, detecting and matching features between images, estimating homographies to relate the images, generating blended intermediate frames, and creating a video from the sequence of frames. It also provides details on steps like feature detection and description, matching features, estimating homographies, image blending, and writing video files.
This document discusses time-of-flight cameras and range imaging. It explains that time-of-flight cameras work by illuminating a scene with amplitude modulated light and measuring the phase difference between the transmitted and reflected light, which encodes distance information. It describes the correlation process used to measure distance at each pixel and discusses sources of error such as multipath interference and temperature drift. Real data examples from a 120x160 sensor are shown. Applications discussed include uses in the Kinect, 3D scanning, and potential future uses in mobile phones.
This document provides an overview of the Leap Motion controller and its capabilities for tracking hand gestures and finger positions. It explains how to set up a basic Leap Motion application using a 2D canvas, initialize the Leap controller, and include an animation loop to continuously draw hand tracking data. Examples are given for visualizing the Leap geometric system, common gestures like swipes and taps, and hand parameters using online code snippets and demos.
This document discusses various types of 3D displays. It begins with an overview of depth cues that can be presented to the human visual system, both monocular cues like size and occlusion, as well as binocular cues like retinal disparity and convergence. The document then presents a taxonomy of 3D display technologies, categorizing them as either glasses-bound or unencumbered designs. Specific display types are described in more detail, including head-mounted displays, spatial and temporal multiplexing, parallax barriers, integral imaging, and volumetric and holographic displays. Multi-view rendering techniques for generating stereoscopic images are also covered, such as using OpenGL for anaglyph generation and off-axis perspective projection.
The document discusses the development of a True HDR app for iPhone. It captures scenes that the human eye can see but most cameras cannot by computationally merging multiple exposures of the same scene. Key challenges included automatically aligning photos with different exposures, merging them naturally without artifacts, managing memory constraints on mobile, and processing images quickly. While popular for a time, updates were rejected by Apple for 8 months, though it provided lessons learned.
OpenCV is an open-source library for computer vision and machine learning. The document discusses OpenCV's features including its modular structure, common computer vision algorithms like Canny edge detection, Hough transform, and cascade classifiers. Code examples are provided to demonstrate how to implement these algorithms using OpenCV functions and data types.
More from Camera Culture Group, MIT Media Lab (20)
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
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.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
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).
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
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
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
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.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
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.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Driving Business Innovation: Latest Generative AI Advancements & Success Story
CORNAR: Looking Around Corners using Trillion FPS Imaging
1. Raskar, Camera Culture, MIT Media Lab
Computational Light Transport:
CORNAR: Looking Around Corners
Camera Culture using
Trillion FPS Imaging
Ramesh Raskar
Ramesh Raskar
MIT Media Lab http://raskar.info/cornar
8. Co-designing Optical and Digital Processing
Computational
Optics
Light Transport
Photon Hacking
Displays
Sensors Computational
Illumination Photography
Signal Processing
Computer Vision
Machine Learning
Bit Hacking
10. CORNAR: Femto-Photography
FemtoFlash
Trillion FPS camera
With M Bawendi,
MIT Chemistry
Serious Sync
Computational Optics
•2012: 3D around a corner (NatureComm, Velten, et. al.)
•2011: Material Sensing (Siggraph Asia, Naik, Zhao, Velten, Raskar, Bala)
•2011: DARPA Young Faculty Award
•2011: Motion Sensing (CVPR, Pandharkar, Velten, Bardagjy, Bawendi, Raskar)
•2009: Hidden barcode (Kirmani, Hutchinson, Davis, Raskar, ICCV’2009)
•2008: Indirect depth (Hirsch, Raskar)
•2008: Transient Light Transport (Raskar, Davis, March 2008)
11. Inverting Light Transport
Multiple Scattering Direct/Global
[Seitz , Kutulakos, Matsushita 2005] [Nayar, Raskar et al 2006]
[Atcheson et al 2008]
[Kutulakos, Steger 2005]
Dual Photography LIDAR
[Sen et al 2005]
18. Why Pico-second Resolution?
ToF Diff = 0.15 mm
s2
1cm
s1
Occluder
3rd bounce
Streak-
camera
C p1
p2
1st bounce
Curse of Pythagoras
19. z
S x
L
R
s
Occluder
Streak-
camera
3rd bounce
Streak Photo
C Laser
B beam
Echoes of Light
20. Trillion FPS
ToF Streak Tube = Inverse of CRT
Very accurate sync
1D camera: Single scan line stretched vertically in time
~2 ps resolution, 480 lines ~= 1 ns
But for small samples in biochemistry
22. Time Image of a single point
Time, ~2ns each row
Space, 640 pixels
Third Bounce (First bounce not shown)
23.
24.
25. 3D shape result from
synthetic data
Forward Reconstruction Invertibility Analysis
Wavefront Non-linear Scene Priors Resolution and
Propagation Inversion dimensions
26. Steady State 4D
[Kajiya, 1986] [Seitz.., 2005]
Impulse Response, 5D
[Raskar and Davis, 2007]
27. Time Resolved Multi-path Imaging
Scene with
hidden elements Ultra fast illumination and camera
5D Raw
Capture Time
profiles
Signal
Proc.
Photo, geometry,
reflectance Novel light transport
beyond models and inference
line of sight algorithms →
t
3D Time images
53. http://raskar.info
Femto-Photography
Looking Around the Corner
BRDF Detection
Trillion FPS
Movies
Space-time Transforms
Editor's Notes
The idea is to use the multiple bounces of light i.e. echoes of light.
My work involves creative new ways to play with light by co-designing optical and digital processing. My work lies at the INTERSECTION of processing of photons and processing of bits. At MERL, I transformed the field of computational photography, with key papers and impact on products At Media Lab, I invented a new field ‘computational light transport’
My idea is to use the multiple bounces of light i.e. echoes of light.
This new form of imaging is possible by fusion of dissimilar .. A specialized camera previously used only in biochemistry labs and a new computational method that analyzes multiple bounces of light. I started the project just before I joined MIT in summer 2008. The hardware we use is borrowed and is in the lab of Prof Bawendi, MIT Chemistry, who is now a collaborator
Here is the pipeline of how we see around corners. We have developed all the mathematical theory and now pushing into the physical experiments.
The original formulation was in the Raskar, Davis paper in 2007.
Here is a road map for this ambitious research project based on time-resolved imaging .. Non line of sight Looking around corner (LaC) is just one example .. Such Time resolved imaging requires one to develop a completely new set of tool for understanding our world. This is a project I started just before coming to MIT in 2008 via an NSF proposal.
The reconstruction back in Fall 2010 was very low, about 80x80 pixels. So these are just baby steps. Top: synthetic results based on physically realistic simulations Bottom: real world results
Top: synthetic results based on physically realistic simulations Bottom: real world results
New results
We can also infer reflectance and albedo Started working on a paper after a casual conversation between Raskar and Kavita Bala