This document discusses generating a three-dimensional panoramic image from a stereo pair of panoramic views of a scene. It begins by introducing binocular vision and how humans perceive depth and 3D using two eyes. It then discusses various methods for generating synthetic 3D effects, including anaglyph images which superimpose stereo image pairs in different colors viewed through colored glasses. The document outlines the process for generating anaglyph images from stereo panoramic views, including computing image disparity and depth from camera parameters. It concludes that generating a 3D panoramic image could enable new applications like panoramic television with depth perception.
Disparity map generation based on trapezoidal camera architecture for multi v...ijma
This document discusses disparity map generation using a trapezoidal camera architecture for multi-view video. It proposes arranging cameras in a trapezoidal configuration to address issues like occlusion. The trapezoidal camera architecture allows cameras to be positioned at different vertical levels, providing multiple viewpoints of occluded areas. It also facilitates accurate computation of parameters like baseline separation between cameras that are important for depth map generation and view synthesis. The document reviews existing parallel, convergent and divergent camera architectures and provides mathematical descriptions to analyze the proposed trapezoidal configuration.
Effective segmentation of sclera, iris and pupil in noisy eye imagesTELKOMNIKA JOURNAL
In today’s sensitive environment, for personal authentication, iris recognition is the most attentive
technique among the various biometric technologies. One of the key steps in the iris recognition system is
the accurate iris segmentation from its surrounding noises including pupil and sclera of a captured
eye-image. In our proposed method, initially input image is preprocessed by using bilateral filtering.
After the preprocessing of images contour based features such as, brightness, color and texture features
are extracted. Then entropy is measured based on the extracted contour based features to effectively
distinguishing the data in the images. Finally, the convolution neural network (CNN) is used for
the effective sclera, iris and pupil parts segmentations based on the entropy measure. The proposed
results are analyzed to demonstrate the better performance of the proposed segmentation method than
the existing methods.
Depth Estimation from Defocused Images: a SurveyIJAAS Team
An important step in 3D data generation is the generation of depth map. Depth map is a black and white image which has exactly the same size of the original captured 2D image that indicates the relative distance of each pixel from the observer to the objects in the real world. This paper presents a survey of Depth Perception from Defocused or blurs images as well as image from motion. The change of distance of the object from the camera has direct relation with the amount of blurring of object in the image. The amount of blurring will be calculated with a comparison in front of the camera directly and can be seen with the changes at gray level around the edges of objects.
This document discusses image deblurring techniques. It begins by introducing image restoration and focusing on image deblurring. It then discusses challenges with image deblurring being an ill-posed problem. It reviews existing approaches to screen image deconvolution including estimating point spread functions and iteratively estimating blur kernels and sharp images. The document also discusses handling spatially variant blur and summarizes the relationship between the proposed method and previous work for different blur types. It proposes using color filters in the aperture to exploit parallax cues for segmentation and blur estimation. Finally, it proposes moving the image sensor circularly during exposure to prevent high frequency attenuation from motion blur.
The document describes a novel method for localizing the pupil in eye gaze tracking systems. The proposed method fuses existing pupil localization techniques, including Hough transform, gray projection, and coarse positioning. This fusion approach aims to improve localization accuracy while lowering false detections. The method first preprocesses the eye image using filtering, edge detection, and thresholding/binarization. It then applies the fused techniques of Hough transform, gray projection, and coarse positioning to the preprocessed image to accurately detect the pupil boundary and center coordinates in a robust manner. The results are expected to provide better pupil localization compared to existing individual techniques.
Computer Vision Based 3D Reconstruction : A ReviewIJECEIAES
3D reconstruction are used in many fields starts from the object reconstruction such as site, and cultural artifacts in both ground and under the sea levels. The scientist are beneficial for these task in order to learn and keep the environment into 3D data due to the extinction. In this paper explained vision setup that is commonly used such as single camera, stereo camera, Kinect / Structured Light/ Time of Flight camera and fusion approach. The prior works also explained how the 3D reconstruction perform in many fields and using various algorithms.
IRIS BIOMETRIC RECOGNITION SYSTEM EMPLOYING CANNY OPERATORcscpconf
Biometrics has become important in security applications. In comparison with many other biometric features, iris recognition has very high recognition accuracy because it depends on
iris which is located in a place that still stable throughout human life and the probability to find two identical iris's is close to zero. The identification system consists of several stages including
segmentation stage which is the most serious and critical one. The current segmentation methods still have limitation in localizing the iris due to circular shape consideration of the
pupil. In this research, Daugman method is done to investigate the segmentation techniques. Eyelid detection is another step that has been included in this study as a part of segmentation
stage to localize the iris accurately and remove unwanted area that might be included. The obtained iris region is encoded using haar wavelets to construct the iris code, which contains
the most discriminating feature in the iris pattern. Hamming distance is used for comparison of iris templates in the recognition stage. The dataset which is used for the study is UBIRIS database. A comparative study of different edge detector operator is performed. It is observed that canny operator is best suited to extract most of the edges to generate the iris code for comparison. Recognition rate of 89% and rejection rate of 95% is achieved.
Purkinje imaging for crystalline lens density measurementPetteriTeikariPhD
Brief introduction for the non-invasive, inexpensive and fast Purkinje image -based method for measuring the spectral transmittance of the human crystalline lens density in vivo.
Alternative download link:
https://www.dropbox.com/s/588y7epy13n34xo/purkinje_imaging.pdf?dl=0
Disparity map generation based on trapezoidal camera architecture for multi v...ijma
This document discusses disparity map generation using a trapezoidal camera architecture for multi-view video. It proposes arranging cameras in a trapezoidal configuration to address issues like occlusion. The trapezoidal camera architecture allows cameras to be positioned at different vertical levels, providing multiple viewpoints of occluded areas. It also facilitates accurate computation of parameters like baseline separation between cameras that are important for depth map generation and view synthesis. The document reviews existing parallel, convergent and divergent camera architectures and provides mathematical descriptions to analyze the proposed trapezoidal configuration.
Effective segmentation of sclera, iris and pupil in noisy eye imagesTELKOMNIKA JOURNAL
In today’s sensitive environment, for personal authentication, iris recognition is the most attentive
technique among the various biometric technologies. One of the key steps in the iris recognition system is
the accurate iris segmentation from its surrounding noises including pupil and sclera of a captured
eye-image. In our proposed method, initially input image is preprocessed by using bilateral filtering.
After the preprocessing of images contour based features such as, brightness, color and texture features
are extracted. Then entropy is measured based on the extracted contour based features to effectively
distinguishing the data in the images. Finally, the convolution neural network (CNN) is used for
the effective sclera, iris and pupil parts segmentations based on the entropy measure. The proposed
results are analyzed to demonstrate the better performance of the proposed segmentation method than
the existing methods.
Depth Estimation from Defocused Images: a SurveyIJAAS Team
An important step in 3D data generation is the generation of depth map. Depth map is a black and white image which has exactly the same size of the original captured 2D image that indicates the relative distance of each pixel from the observer to the objects in the real world. This paper presents a survey of Depth Perception from Defocused or blurs images as well as image from motion. The change of distance of the object from the camera has direct relation with the amount of blurring of object in the image. The amount of blurring will be calculated with a comparison in front of the camera directly and can be seen with the changes at gray level around the edges of objects.
This document discusses image deblurring techniques. It begins by introducing image restoration and focusing on image deblurring. It then discusses challenges with image deblurring being an ill-posed problem. It reviews existing approaches to screen image deconvolution including estimating point spread functions and iteratively estimating blur kernels and sharp images. The document also discusses handling spatially variant blur and summarizes the relationship between the proposed method and previous work for different blur types. It proposes using color filters in the aperture to exploit parallax cues for segmentation and blur estimation. Finally, it proposes moving the image sensor circularly during exposure to prevent high frequency attenuation from motion blur.
The document describes a novel method for localizing the pupil in eye gaze tracking systems. The proposed method fuses existing pupil localization techniques, including Hough transform, gray projection, and coarse positioning. This fusion approach aims to improve localization accuracy while lowering false detections. The method first preprocesses the eye image using filtering, edge detection, and thresholding/binarization. It then applies the fused techniques of Hough transform, gray projection, and coarse positioning to the preprocessed image to accurately detect the pupil boundary and center coordinates in a robust manner. The results are expected to provide better pupil localization compared to existing individual techniques.
Computer Vision Based 3D Reconstruction : A ReviewIJECEIAES
3D reconstruction are used in many fields starts from the object reconstruction such as site, and cultural artifacts in both ground and under the sea levels. The scientist are beneficial for these task in order to learn and keep the environment into 3D data due to the extinction. In this paper explained vision setup that is commonly used such as single camera, stereo camera, Kinect / Structured Light/ Time of Flight camera and fusion approach. The prior works also explained how the 3D reconstruction perform in many fields and using various algorithms.
IRIS BIOMETRIC RECOGNITION SYSTEM EMPLOYING CANNY OPERATORcscpconf
Biometrics has become important in security applications. In comparison with many other biometric features, iris recognition has very high recognition accuracy because it depends on
iris which is located in a place that still stable throughout human life and the probability to find two identical iris's is close to zero. The identification system consists of several stages including
segmentation stage which is the most serious and critical one. The current segmentation methods still have limitation in localizing the iris due to circular shape consideration of the
pupil. In this research, Daugman method is done to investigate the segmentation techniques. Eyelid detection is another step that has been included in this study as a part of segmentation
stage to localize the iris accurately and remove unwanted area that might be included. The obtained iris region is encoded using haar wavelets to construct the iris code, which contains
the most discriminating feature in the iris pattern. Hamming distance is used for comparison of iris templates in the recognition stage. The dataset which is used for the study is UBIRIS database. A comparative study of different edge detector operator is performed. It is observed that canny operator is best suited to extract most of the edges to generate the iris code for comparison. Recognition rate of 89% and rejection rate of 95% is achieved.
Purkinje imaging for crystalline lens density measurementPetteriTeikariPhD
Brief introduction for the non-invasive, inexpensive and fast Purkinje image -based method for measuring the spectral transmittance of the human crystalline lens density in vivo.
Alternative download link:
https://www.dropbox.com/s/588y7epy13n34xo/purkinje_imaging.pdf?dl=0
Performance analysis on color image mosaicing techniques on FPGAIJECEIAES
Today, the surveillance systems and other monitoring systems are considering the capturing of image sequences in a single frame. The captured images can be combined to get the mosaiced image or combined image sequence. But the captured image may have quality issues like brightness issue, alignment issue (correlation issue), resolution issue, manual image registration issue etc. The existing technique like cross correlation can offer better image mosaicing but faces brightness issue in mosaicing. Thus, this paper introduces two different methods for mosaicing i.e., (a) Sliding Window Module (SWM) based Color Image Mosaicing (CIM) and (b) Discrete Cosine Transform (DCT) based CIM on Field Programmable Gate Array (FPGA). The SWM based CIM adopted for corner detection of two images and perform the automatic image registration while DCT based CIM aligns both the local as well as global alignment of images by using phase correlation approach. Finally, these two methods performances are analyzed by comparing with parameters like PSNR, MSE, device utilization and execution time. From the analysis it is concluded that the DCT based CIM can offers significant results than SWM based CIM.
A novel equalization scheme for the selective enhancement of optical disc and...TELKOMNIKA JOURNAL
The ratio of the diameters of Optic Cup (OC) and Optic Disc (OD), termed as ‘Cup to Disc Ratio’
(CDR), derived from the fundus imagery is a popular biomarker used for the diagnosis of glaucoma.
Demarcation of OC and OD either manually or through automated image processing algorithms is error
prone because of poor grey level contrast and their vague boundaries. A dedicated equalization which
simultaneously compresses the dynamic range of the background and stretches the range of ODis
proposed in this paper. Unlike the conventional GHE, in the proposed equalization, the original histogram
is inverted and weighted nonlinearly before computing the Cumulative Probability Density (CPD).
The equalization scheme is compared with Adaptive Histogram Equalization (AHE), Global Histogram
Equalization (GHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) in terms of the
difference between the mean grey levels of OD and the background, using a quantitative metric known as
Contrast Improvement Index (CII). The CII exhibited by CLAHE, GHE and the proposed scheme are
1.1977 ± 0.0326, 1.0862 ± 0.0304 and 1.3312 ± 0.0486, respectively.The proposed method is observed to
be superior to CLAHE, GHE and AHE and it can be employed in Computerized Clinical Decision Support
Systems (CCDSS) to improve the accuracy of localizing the OD and the computation of CDR.
Automatic 3D view Generation from a Single 2D Image for both Indoor and Outdo...ijcsa
This document discusses algorithms for automatically generating 3D video views from a single 2D image of both indoor and outdoor scenes. For indoor scenes, it segments the floor to determine the termination point for video generation. For outdoor scenes, it detects the vanishing point, which is used to calculate the distance to the termination point. The algorithms crop the input image to generate frames as it navigates up to the termination point, creating the effect of a 3D video view from a single 2D image with no need for human intervention. Experimental results on over 250 images demonstrated the effectiveness of the proposed methods.
Interactive full body motion capture using infrared sensor networkijcga
Traditional motion capture (mocap) has been
well
-
stud
ied in visual science for
the last decades
. However
the fie
ld is mostly about capturing
precise animation to be used in
specific
application
s
after
intensive
post
processing such as studying biomechanics or rigging models in movies. These data set
s are normally
captured in complex laboratory environments with
sophisticated
equipment thus making motion capture a
field that is mostly exclusive to professional animators.
In
addition
, obtrusive sensors must be attached to
actors and calibrated within t
he capturing system, resulting in limited and unnatural motion.
In recent year
the rise of computer vision and interactive entertainment opened the gate for a different type of motion
capture which focuses on producing
optical
marker
less
or mechanical sens
orless
motion capture.
Furtherm
ore a wide array of low
-
cost
device are released that are easy to use
for less mission critical
applications
.
This paper
describe
s
a new technique of using multiple infrared devices to process data from
multiple infrared sensors to enhance the flexibility and accuracy of the markerless mocap
using commodity
devices such as Kinect
. The method involves analyzing each individual sensor
data, decompose and rebuild
them into a uniformed skeleton across all sensors. We then assign criteria to define the confidence level of
captured signal from
sensor. Each sensor operates on its own process and communicates through MPI.
Our method emphasize
s on the need of minimum calculation overhead for better real time performance
while being able to maintain good scalability
Stereo Vision Human Motion Detection and Tracking in Uncontrolled EnvironmentTELKOMNIKA JOURNAL
Stereo vision in detecting human motion is an emerging research for automation, robotics, and sports science field due to the advancement of imaging sensors and information technology. The difficulty of human motion detection and tracking is relatively complex when it is applied to uncontrolled environment. In this paper, a hybrid filter approach is proposed to detect human motion in the stereo vision. The hybrid filter approach integrates Gaussian filter and median filter to reduce the coverage of shadow and sudden change of illumination. In addition, sequential thinning and thickening morphological method is used to construct the skeleton model. The proposed hybrid approach is compared with the normalized filter. As a result, the proposed approach produces better skeleton model with less influential effect on shadow and illumination. The output results of the proposed approach can show up to 86% of average accuracy matched with skeleton model. In addition, obtains approximately 94% of sensitivity measurement in the stereo vision. The proposed approach using hybrid filter and sequential morphology could improve the performance of the detection in the uncontrolled environment.
Coutinho A Depth Compensation Method For Cross Ratio Based Eye TrackingKalle
Traditional cross-ratio methods (TCR) project a light pattern and use invariant properties of projective geometry to estimate the gaze position. Advantages of the TCR methods include robustness to large head movements and in general requires just a one time per user calibration. However, the accuracy of TCR methods decay significantly for head movements along the camera optical axis, mainly due to the angular difference between the optical and visual axis of the eye. In this paper we propose a depth compensation cross-ratio (DCR) method that improves the accuracy of TCR methods for large head depth variations. Our solution compensates the angular offset using a 2D onscreen vector computed from a simple calibration procedure. The length of the 2D vector, which varies with head distance, is adjusted by a scale factor that is estimated from relative size variations of the corneal reflection pattern. The proposed DCR solution was compared to a TCR method using synthetic and real data from 2 users. An average improvement of 40% was observed with synthetic data, and 8% with the real data.
RECOGNITION OF RECAPTURED IMAGES USING PHYSICAL BASED FEATUREScsandit
With the development of multimedia technology and digital devices, it is very simple and easier to recapture a high quality images from LCD screens. In authentication, the use of such
recaptured images can be very dangerous. So, it is very important to recognize the recaptured images in order to increase authenticity. Image recapture detection (IRD) is to distinguish realscene images from the recaptured ones. An image recapture detection method based on set of physical based features is proposed in this paper, which uses combination of low-level features including texture, HSV colour and blurriness. Twenty six dimensions of features are xtracted to train a suppo rt vector machine classifier with linear kernel. The experimental results show that the proposed method is efficient with good recognition rate of distinguishing real scene images from the recaptured ones. The proposed method also possesses low dimensional features compared to the state-of-the-art recaptured methods.
Interactive Full-Body Motion Capture Using Infrared Sensor Network ijcga
The document describes a new technique for interactive full-body motion capture using multiple infrared sensors. It processes data from each sensor independently and then combines the results to enhance flexibility and accuracy. The method aims to maintain real-time performance while improving on issues like limited actor orientation, inaccurate joint tracking, and conflicting data from individual sensors.
THE EFFECT OF PHYSICAL BASED FEATURES FOR RECOGNITION OF RECAPTURED IMAGESijcsit
It is very simple and easier to recapture a high quality images from LCD screens with the development of multimedia technology and digital devices. In authentication, the use of such recaptured images can be very dangerous. So, it is very important to recognize the recaptured images in order to increase authenticity. Even though, there are a number of features that have been proposed in various state-of-theart
visual recognition tasks, but it is still difficult to decide which feature or combination of features have more significant impact on this task. In this paper an image recapture detection method based on set of physical based features including texture, HSV colour and blurriness is proposed. Also, this paper evaluates the performance of different distinctive featuresin the context of recognition of recaptured
images. Several experimental setups have been conducted in order to demonstrate the performance of the proposed method. In all these experimental results, the proposed method is efficient with good recognition rate. Among the combination of low-level features, CS-LBP detection is to operator which is used to extract the texture feature is the most robust feature.
VIDEO SEGMENTATION FOR MOVING OBJECT DETECTION USING LOCAL CHANGE & ENTROPY B...csandit
Motion detection and object segmentation are an important research area of image-video
processing and computer vision. The technique and mathematical modeling used to detect and
segment region of interest (ROI) objects comprise the algorithmic modules of various high-level
techniques in video analysis, object extraction, classification, and recognition. The detection of
moving object is significant in many tasks, such as video surveillance & moving object tracking.
The design of a video surveillance system is directed on involuntary identification of events of
interest, especially on tracking and on classification of moving objects. An entropy based realtime
adaptive non-parametric window thresholding algorithm for change detection is
anticipated in this research. Based on the approximation of the value of scatter of sections of
change in a difference image, a threshold of every image block is calculated discriminatively
using entropy structure, and then the global threshold is attained by averaging all thresholds for
image blocks of the frame. The block threshold is calculated contrarily for regions of change
and background. Investigational results show the proposed thresholding algorithm
accomplishes well for change detection with high efficiency.
IRJET- A Comprehensive Study on Image Defogging TechniquesIRJET Journal
This document summarizes techniques for removing haze and other pollutants from images. It discusses using a dark channel prior method based on observations that at least one color channel has pixels with low values. Transmission maps and atmospheric light can be estimated using this dark channel prior. The document also discusses using depth estimation, wavelet-based techniques, enhancement-based techniques, filtering-based techniques, supervised learning-based techniques, fusion-based techniques, and meta-heuristic system-based techniques for haze removal. It provides an overview of these different haze removal techniques.
This doctoral dissertation examines facial skin motion properties from video for modeling and applications. It presents two methods for computing strain patterns from video: a finite difference method and a finite element method. The finite element method incorporates material properties of facial tissues by modeling their Young's modulus values. Experiments show strain patterns are discriminative and stable features for facial expression recognition, age estimation, and person identification. The dissertation also develops a method for expression invariant face matching by modeling Young's modulus from multiple expressions.
Possible future avenues for ophthalmic imaging combining advanced techniques and deep learning. "Bubbling under the surface, and inspiration from ‘bioimaging’ in general"
IRJET- Performance Analysis of Learning Algorithms for Automated Detection of...IRJET Journal
This document presents research on using machine learning algorithms to detect glaucoma from fundus images. The researchers extracted various texture and intensity features from fundus images using methods like gray level co-occurrence matrix, histogram of oriented gradients, wavelet transforms, and shearlet transforms. They used feature selection to reduce the number of features before classifying the images as normal or glaucomatous using support vector machines and K-nearest neighbors algorithms. The best accuracy of 97.5% was achieved using wavelet features. The researchers evaluated the classification performance using metrics like accuracy, sensitivity, specificity, and predictive values to assess the ability of the extracted features to detect glaucoma.
Proposed Multi-object Tracking Algorithm Using Sobel Edge Detection operatorQUESTJOURNAL
ABSTRACT:Tracking of moving objects that is called video tracking is used for measuring motion parameters and obtaining a visual record of the moving objects, it is an important area of application in image processing. In general there are two different approaches to obtain object tracking: the first is Recognition-based Tracking, and the second is the Motion-based Tracking. Video tracking system raises a wide possibility in today’s society. This system is used in various applications such as military, security, monitoring, robotic, and nowadays in dayto-day applications. However the video tracking systems still have many open problems and various research activities in a video tracking system are explores. This paper presents an algorithm for video tracking of any moving targets with the uses of contour based detection technique that depends on the sobel operator. The proposed system is suitable for indoor and outdoor applications. Our approach has the advantage of extending the applicability of tracking system and also, as presented here improves the performance of the tracker making feasible high frame rate video tracking. The goal of the tracking system is to analyze the video frames and estimate the position of a part of the input video frame (usually a moving object), our approach can detect, tracked any object more than one object and calculate the position of the moving objects. Therefore, the aim of this paper is to construct a motion tracking system for moving objects. Where, at the end of this paper, the detail outcome and result are discussed using experiments results of the proposed technique
DISPARITY MAP GENERATION BASED ON TRAPEZOIDAL CAMERA ARCHITECTURE FOR MULTI-V...ijma
Visual content acquisition is a strategic functional block of any visual system. Despite its wide possibilities,
the arrangement of cameras for the acquisition of good quality visual content for use in multi-view video
remains a huge challenge. This paper presents the mathematical description of trapezoidal camera
architecture and relationships which facilitate the determination of camera position for visual content
acquisition in multi-view video, and depth map generation. The strong point of Trapezoidal Camera
Architecture is that it allows for adaptive camera topology by which points within the scene, especially the
occluded ones can be optically and geometrically viewed from several different viewpoints either on the
edge of the trapezoid or inside it. The concept of maximum independent set, trapezoid characteristics, and
the fact that the positions of cameras (with the exception of few) differ in their vertical coordinate
description could very well be used to address the issue of occlusion which continues to be a major
problem in computer vision with regards to the generation of depth map.
Augmented Reality in Volumetric Medical Imaging Using Stereoscopic 3D Display ijcga
This paper is written about augmented reality in medicine. Medical imaging equipment (CT, PET, MRI) are produced 3D volumetric data, so using the stereoscopic 3D display, observer feels depth perception. The major factors about depth-Convergence, Accommodation, Relative size are tested. Convergence and Accommodation have affected depth perception but relative size is negligible.
A UGMENT R EALITY IN V OLUMETRIC M EDICAL I MAGING U SING S TEREOSCOPIC...ijcga
This document discusses using stereoscopic 3D displays to view volumetric medical imaging data in augmented reality. It summarizes an experiment that tested how three factors - convergence, accommodation, and relative size - affect depth perception when viewing 3D medical images on a stereoscopic display. The experiment found that convergence and accommodation significantly impacted depth perception, while relative size had a negligible effect. Viewing images between 227-291mm in front of the screen provided the most effective depth perception.
Real-Time Simulation of Impaired Vision in Naturalistic Settings with Gaze-Co...Margarita Vinnikov
The document describes a Gaze-Contingent Display system that simulates visual field defects to study their effects and educate the public. The system uses eye and head tracking to determine gaze direction and simulate vision loss based on the tracked gaze point. This allows investigation of how visual field defects impact tasks like driving. The system aims to help develop strategies for coping with low vision conditions and increase disease awareness.
Eye Gaze Tracking With a Web Camera in a Desktop Environment1crore projects
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3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
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An intelligent strabismus detection method based on convolution neural networkTELKOMNIKA JOURNAL
Strabismus is one of the widespread vision disorders in which the eyes are misaligned and asymmetric. Convolutional neural networks (CNNs) are properly designed for analyzing images and detecting texture patterns. In this paper, we proposed a system that uses deep learning CNN applications for automatically detecting and classifying strabismus disorder. The proposed system includes two main stages: first, the detection of facial eye segmentation using the viola-jones algorithm. The second stage is to map the segmented eye area according to the iris position of each eye. This method is applied to three strabismus datasets, gathered as digital images. The second section covers the segmentation of the eye region. Besides, the evaluation equations for measuring system performance. The system has undergone numerous experiments in various stages to simulate and analyze the detection performance of CNN layers through different classifiers and variant thresholds ratio. The researchers investigated the experimental outcomes during the training and testing phases and obtained promising results that exhibit the effectiveness of the proposed system. According to the results, the accuracy of this technique reached 95.62%.
Performance analysis on color image mosaicing techniques on FPGAIJECEIAES
Today, the surveillance systems and other monitoring systems are considering the capturing of image sequences in a single frame. The captured images can be combined to get the mosaiced image or combined image sequence. But the captured image may have quality issues like brightness issue, alignment issue (correlation issue), resolution issue, manual image registration issue etc. The existing technique like cross correlation can offer better image mosaicing but faces brightness issue in mosaicing. Thus, this paper introduces two different methods for mosaicing i.e., (a) Sliding Window Module (SWM) based Color Image Mosaicing (CIM) and (b) Discrete Cosine Transform (DCT) based CIM on Field Programmable Gate Array (FPGA). The SWM based CIM adopted for corner detection of two images and perform the automatic image registration while DCT based CIM aligns both the local as well as global alignment of images by using phase correlation approach. Finally, these two methods performances are analyzed by comparing with parameters like PSNR, MSE, device utilization and execution time. From the analysis it is concluded that the DCT based CIM can offers significant results than SWM based CIM.
A novel equalization scheme for the selective enhancement of optical disc and...TELKOMNIKA JOURNAL
The ratio of the diameters of Optic Cup (OC) and Optic Disc (OD), termed as ‘Cup to Disc Ratio’
(CDR), derived from the fundus imagery is a popular biomarker used for the diagnosis of glaucoma.
Demarcation of OC and OD either manually or through automated image processing algorithms is error
prone because of poor grey level contrast and their vague boundaries. A dedicated equalization which
simultaneously compresses the dynamic range of the background and stretches the range of ODis
proposed in this paper. Unlike the conventional GHE, in the proposed equalization, the original histogram
is inverted and weighted nonlinearly before computing the Cumulative Probability Density (CPD).
The equalization scheme is compared with Adaptive Histogram Equalization (AHE), Global Histogram
Equalization (GHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) in terms of the
difference between the mean grey levels of OD and the background, using a quantitative metric known as
Contrast Improvement Index (CII). The CII exhibited by CLAHE, GHE and the proposed scheme are
1.1977 ± 0.0326, 1.0862 ± 0.0304 and 1.3312 ± 0.0486, respectively.The proposed method is observed to
be superior to CLAHE, GHE and AHE and it can be employed in Computerized Clinical Decision Support
Systems (CCDSS) to improve the accuracy of localizing the OD and the computation of CDR.
Automatic 3D view Generation from a Single 2D Image for both Indoor and Outdo...ijcsa
This document discusses algorithms for automatically generating 3D video views from a single 2D image of both indoor and outdoor scenes. For indoor scenes, it segments the floor to determine the termination point for video generation. For outdoor scenes, it detects the vanishing point, which is used to calculate the distance to the termination point. The algorithms crop the input image to generate frames as it navigates up to the termination point, creating the effect of a 3D video view from a single 2D image with no need for human intervention. Experimental results on over 250 images demonstrated the effectiveness of the proposed methods.
Interactive full body motion capture using infrared sensor networkijcga
Traditional motion capture (mocap) has been
well
-
stud
ied in visual science for
the last decades
. However
the fie
ld is mostly about capturing
precise animation to be used in
specific
application
s
after
intensive
post
processing such as studying biomechanics or rigging models in movies. These data set
s are normally
captured in complex laboratory environments with
sophisticated
equipment thus making motion capture a
field that is mostly exclusive to professional animators.
In
addition
, obtrusive sensors must be attached to
actors and calibrated within t
he capturing system, resulting in limited and unnatural motion.
In recent year
the rise of computer vision and interactive entertainment opened the gate for a different type of motion
capture which focuses on producing
optical
marker
less
or mechanical sens
orless
motion capture.
Furtherm
ore a wide array of low
-
cost
device are released that are easy to use
for less mission critical
applications
.
This paper
describe
s
a new technique of using multiple infrared devices to process data from
multiple infrared sensors to enhance the flexibility and accuracy of the markerless mocap
using commodity
devices such as Kinect
. The method involves analyzing each individual sensor
data, decompose and rebuild
them into a uniformed skeleton across all sensors. We then assign criteria to define the confidence level of
captured signal from
sensor. Each sensor operates on its own process and communicates through MPI.
Our method emphasize
s on the need of minimum calculation overhead for better real time performance
while being able to maintain good scalability
Stereo Vision Human Motion Detection and Tracking in Uncontrolled EnvironmentTELKOMNIKA JOURNAL
Stereo vision in detecting human motion is an emerging research for automation, robotics, and sports science field due to the advancement of imaging sensors and information technology. The difficulty of human motion detection and tracking is relatively complex when it is applied to uncontrolled environment. In this paper, a hybrid filter approach is proposed to detect human motion in the stereo vision. The hybrid filter approach integrates Gaussian filter and median filter to reduce the coverage of shadow and sudden change of illumination. In addition, sequential thinning and thickening morphological method is used to construct the skeleton model. The proposed hybrid approach is compared with the normalized filter. As a result, the proposed approach produces better skeleton model with less influential effect on shadow and illumination. The output results of the proposed approach can show up to 86% of average accuracy matched with skeleton model. In addition, obtains approximately 94% of sensitivity measurement in the stereo vision. The proposed approach using hybrid filter and sequential morphology could improve the performance of the detection in the uncontrolled environment.
Coutinho A Depth Compensation Method For Cross Ratio Based Eye TrackingKalle
Traditional cross-ratio methods (TCR) project a light pattern and use invariant properties of projective geometry to estimate the gaze position. Advantages of the TCR methods include robustness to large head movements and in general requires just a one time per user calibration. However, the accuracy of TCR methods decay significantly for head movements along the camera optical axis, mainly due to the angular difference between the optical and visual axis of the eye. In this paper we propose a depth compensation cross-ratio (DCR) method that improves the accuracy of TCR methods for large head depth variations. Our solution compensates the angular offset using a 2D onscreen vector computed from a simple calibration procedure. The length of the 2D vector, which varies with head distance, is adjusted by a scale factor that is estimated from relative size variations of the corneal reflection pattern. The proposed DCR solution was compared to a TCR method using synthetic and real data from 2 users. An average improvement of 40% was observed with synthetic data, and 8% with the real data.
RECOGNITION OF RECAPTURED IMAGES USING PHYSICAL BASED FEATUREScsandit
With the development of multimedia technology and digital devices, it is very simple and easier to recapture a high quality images from LCD screens. In authentication, the use of such
recaptured images can be very dangerous. So, it is very important to recognize the recaptured images in order to increase authenticity. Image recapture detection (IRD) is to distinguish realscene images from the recaptured ones. An image recapture detection method based on set of physical based features is proposed in this paper, which uses combination of low-level features including texture, HSV colour and blurriness. Twenty six dimensions of features are xtracted to train a suppo rt vector machine classifier with linear kernel. The experimental results show that the proposed method is efficient with good recognition rate of distinguishing real scene images from the recaptured ones. The proposed method also possesses low dimensional features compared to the state-of-the-art recaptured methods.
Interactive Full-Body Motion Capture Using Infrared Sensor Network ijcga
The document describes a new technique for interactive full-body motion capture using multiple infrared sensors. It processes data from each sensor independently and then combines the results to enhance flexibility and accuracy. The method aims to maintain real-time performance while improving on issues like limited actor orientation, inaccurate joint tracking, and conflicting data from individual sensors.
THE EFFECT OF PHYSICAL BASED FEATURES FOR RECOGNITION OF RECAPTURED IMAGESijcsit
It is very simple and easier to recapture a high quality images from LCD screens with the development of multimedia technology and digital devices. In authentication, the use of such recaptured images can be very dangerous. So, it is very important to recognize the recaptured images in order to increase authenticity. Even though, there are a number of features that have been proposed in various state-of-theart
visual recognition tasks, but it is still difficult to decide which feature or combination of features have more significant impact on this task. In this paper an image recapture detection method based on set of physical based features including texture, HSV colour and blurriness is proposed. Also, this paper evaluates the performance of different distinctive featuresin the context of recognition of recaptured
images. Several experimental setups have been conducted in order to demonstrate the performance of the proposed method. In all these experimental results, the proposed method is efficient with good recognition rate. Among the combination of low-level features, CS-LBP detection is to operator which is used to extract the texture feature is the most robust feature.
VIDEO SEGMENTATION FOR MOVING OBJECT DETECTION USING LOCAL CHANGE & ENTROPY B...csandit
Motion detection and object segmentation are an important research area of image-video
processing and computer vision. The technique and mathematical modeling used to detect and
segment region of interest (ROI) objects comprise the algorithmic modules of various high-level
techniques in video analysis, object extraction, classification, and recognition. The detection of
moving object is significant in many tasks, such as video surveillance & moving object tracking.
The design of a video surveillance system is directed on involuntary identification of events of
interest, especially on tracking and on classification of moving objects. An entropy based realtime
adaptive non-parametric window thresholding algorithm for change detection is
anticipated in this research. Based on the approximation of the value of scatter of sections of
change in a difference image, a threshold of every image block is calculated discriminatively
using entropy structure, and then the global threshold is attained by averaging all thresholds for
image blocks of the frame. The block threshold is calculated contrarily for regions of change
and background. Investigational results show the proposed thresholding algorithm
accomplishes well for change detection with high efficiency.
IRJET- A Comprehensive Study on Image Defogging TechniquesIRJET Journal
This document summarizes techniques for removing haze and other pollutants from images. It discusses using a dark channel prior method based on observations that at least one color channel has pixels with low values. Transmission maps and atmospheric light can be estimated using this dark channel prior. The document also discusses using depth estimation, wavelet-based techniques, enhancement-based techniques, filtering-based techniques, supervised learning-based techniques, fusion-based techniques, and meta-heuristic system-based techniques for haze removal. It provides an overview of these different haze removal techniques.
This doctoral dissertation examines facial skin motion properties from video for modeling and applications. It presents two methods for computing strain patterns from video: a finite difference method and a finite element method. The finite element method incorporates material properties of facial tissues by modeling their Young's modulus values. Experiments show strain patterns are discriminative and stable features for facial expression recognition, age estimation, and person identification. The dissertation also develops a method for expression invariant face matching by modeling Young's modulus from multiple expressions.
Possible future avenues for ophthalmic imaging combining advanced techniques and deep learning. "Bubbling under the surface, and inspiration from ‘bioimaging’ in general"
IRJET- Performance Analysis of Learning Algorithms for Automated Detection of...IRJET Journal
This document presents research on using machine learning algorithms to detect glaucoma from fundus images. The researchers extracted various texture and intensity features from fundus images using methods like gray level co-occurrence matrix, histogram of oriented gradients, wavelet transforms, and shearlet transforms. They used feature selection to reduce the number of features before classifying the images as normal or glaucomatous using support vector machines and K-nearest neighbors algorithms. The best accuracy of 97.5% was achieved using wavelet features. The researchers evaluated the classification performance using metrics like accuracy, sensitivity, specificity, and predictive values to assess the ability of the extracted features to detect glaucoma.
Proposed Multi-object Tracking Algorithm Using Sobel Edge Detection operatorQUESTJOURNAL
ABSTRACT:Tracking of moving objects that is called video tracking is used for measuring motion parameters and obtaining a visual record of the moving objects, it is an important area of application in image processing. In general there are two different approaches to obtain object tracking: the first is Recognition-based Tracking, and the second is the Motion-based Tracking. Video tracking system raises a wide possibility in today’s society. This system is used in various applications such as military, security, monitoring, robotic, and nowadays in dayto-day applications. However the video tracking systems still have many open problems and various research activities in a video tracking system are explores. This paper presents an algorithm for video tracking of any moving targets with the uses of contour based detection technique that depends on the sobel operator. The proposed system is suitable for indoor and outdoor applications. Our approach has the advantage of extending the applicability of tracking system and also, as presented here improves the performance of the tracker making feasible high frame rate video tracking. The goal of the tracking system is to analyze the video frames and estimate the position of a part of the input video frame (usually a moving object), our approach can detect, tracked any object more than one object and calculate the position of the moving objects. Therefore, the aim of this paper is to construct a motion tracking system for moving objects. Where, at the end of this paper, the detail outcome and result are discussed using experiments results of the proposed technique
DISPARITY MAP GENERATION BASED ON TRAPEZOIDAL CAMERA ARCHITECTURE FOR MULTI-V...ijma
Visual content acquisition is a strategic functional block of any visual system. Despite its wide possibilities,
the arrangement of cameras for the acquisition of good quality visual content for use in multi-view video
remains a huge challenge. This paper presents the mathematical description of trapezoidal camera
architecture and relationships which facilitate the determination of camera position for visual content
acquisition in multi-view video, and depth map generation. The strong point of Trapezoidal Camera
Architecture is that it allows for adaptive camera topology by which points within the scene, especially the
occluded ones can be optically and geometrically viewed from several different viewpoints either on the
edge of the trapezoid or inside it. The concept of maximum independent set, trapezoid characteristics, and
the fact that the positions of cameras (with the exception of few) differ in their vertical coordinate
description could very well be used to address the issue of occlusion which continues to be a major
problem in computer vision with regards to the generation of depth map.
Augmented Reality in Volumetric Medical Imaging Using Stereoscopic 3D Display ijcga
This paper is written about augmented reality in medicine. Medical imaging equipment (CT, PET, MRI) are produced 3D volumetric data, so using the stereoscopic 3D display, observer feels depth perception. The major factors about depth-Convergence, Accommodation, Relative size are tested. Convergence and Accommodation have affected depth perception but relative size is negligible.
A UGMENT R EALITY IN V OLUMETRIC M EDICAL I MAGING U SING S TEREOSCOPIC...ijcga
This document discusses using stereoscopic 3D displays to view volumetric medical imaging data in augmented reality. It summarizes an experiment that tested how three factors - convergence, accommodation, and relative size - affect depth perception when viewing 3D medical images on a stereoscopic display. The experiment found that convergence and accommodation significantly impacted depth perception, while relative size had a negligible effect. Viewing images between 227-291mm in front of the screen provided the most effective depth perception.
Real-Time Simulation of Impaired Vision in Naturalistic Settings with Gaze-Co...Margarita Vinnikov
The document describes a Gaze-Contingent Display system that simulates visual field defects to study their effects and educate the public. The system uses eye and head tracking to determine gaze direction and simulate vision loss based on the tracked gaze point. This allows investigation of how visual field defects impact tasks like driving. The system aims to help develop strategies for coping with low vision conditions and increase disease awareness.
Eye Gaze Tracking With a Web Camera in a Desktop Environment1crore projects
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Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
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2. Ns2 project
3. Embedded project
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An intelligent strabismus detection method based on convolution neural networkTELKOMNIKA JOURNAL
Strabismus is one of the widespread vision disorders in which the eyes are misaligned and asymmetric. Convolutional neural networks (CNNs) are properly designed for analyzing images and detecting texture patterns. In this paper, we proposed a system that uses deep learning CNN applications for automatically detecting and classifying strabismus disorder. The proposed system includes two main stages: first, the detection of facial eye segmentation using the viola-jones algorithm. The second stage is to map the segmented eye area according to the iris position of each eye. This method is applied to three strabismus datasets, gathered as digital images. The second section covers the segmentation of the eye region. Besides, the evaluation equations for measuring system performance. The system has undergone numerous experiments in various stages to simulate and analyze the detection performance of CNN layers through different classifiers and variant thresholds ratio. The researchers investigated the experimental outcomes during the training and testing phases and obtained promising results that exhibit the effectiveness of the proposed system. According to the results, the accuracy of this technique reached 95.62%.
we introduce the perceptual issues relevant to seeing three dimensions in digital imagery. Technological constraints
like limited field-of-view and spatial resolution prevent the display of images that match the real world in all respects.
Therefore, only some elements of real world depth perception are utilized when viewing 3D CGI. Depth Cue Theory is the
main theory of depth perception. It states that different sources of information, or depth cues, combine to give a viewer the 3D
layout of a scene. Alternatively, the Ecological Theory takes a generalized approach to depth perception. It states that the HVS
relies on more than the image on the retina; it requires an examination of the entire state of the viewer and their surroundings
(i.e., the context of viewing). In this paper, we rely on Depth Cue Theory, although we acknowledge the importance of visual
context where appropriate. As seen later, the type of visual environment and the viewer’s task play a significant part in the
effectiveness of a 3D VDS. Both theories assert that there are some basic sources of information about 3D layout. These are
generally divided into three types: pictorial, coulometer and stereo depth cues. The perceptual process by which these cues
combine to form a sense of depth is a complicated and outdebated issue. Different approaches to measuring the ability to
perceive depth have also been posited. We discuss these issues with respect to CGI.
Stereoscopic imaging uses two slightly different images, one for each eye, to give the perception of depth. It originated in the 1800s with the development of stereoscopes and stereo cameras. Today stereoscopic techniques include anaglyph, polarization, and shutter glasses methods. Stereoscopic imaging has applications in entertainment, medicine, space exploration, and more. Future developments may allow glass-free 3D viewing through techniques like autostereoscopy.
The Effectiveness of 2D-3D Converters in Rendering Natural Water Phenomenaidescitation
Several commercially available conversion
applications have been developed to generate 3D content from
existing 2D images or videos. In this study, five 2D-3D
converters are evaluated for their effectiveness in producing
high quality 3D videos with scenery containing water
phenomena. Such scenes are challenging to convert due to
scene complexity including detail, scene dynamics,
illumination, and reflective distortion. Comparisons are given
using quantitative and subjective evaluations.
Human motion is fundamental to understanding behaviour. In spite of advancement on single image 3 Dimensional pose and estimation of shapes, current video-based state of the art methods unsuccessful to produce precise and motion of natural sequences due to inefficiency of ground-truth 3 Dimensional motion data for training. Recognition of Human action for programmed video surveillance applications is an interesting but forbidding task especially if the videos are captured in an unpleasant lighting environment. It is a Spatial-temporal feature-based correlation filter, for concurrent observation and identification of numerous human actions in a little-light environment. Estimated the presentation of a proposed filter with immense experimentation on night-time action datasets. Tentative results demonstrate the potency of the merging schemes for vigorous action recognition in a significantly low light environment.
The document discusses various techniques for detecting tampering in digital images, including passive and active methods. Passive methods analyze underlying pixel statistics and properties to detect inconsistencies introduced during tampering, without requiring embedded watermarks. Specific passive techniques discussed are splicing detection, copy-move detection, and statistical-based detection. The document also briefly covers active techniques like digital watermarking and signatures that require embedded signals but can authenticate images. Overall, the document provides an overview of prominent frameworks for passive image tampering detection and localization.
Removal of Transformation Errors by Quarterion In Multi View Image RegistrationIDES Editor
This method is based upon the image registration
process and the application is when the text which is to be
identified is behind the mesh which works as a hurdle. We
know that the mesh as hurdle can be made less irritating by
either moving the camera or the source itself. The method
uses Radon Transform for extracting the mesh lines and
capturing the position of the mesh lines. The final process of
filling the deformed image is through the registration. The
method is adaptive to movement in any direction. The
transformation errors are removed by the Quarterions. It was
tested on a number of images [200] approximately and gave
excellent results.
3D television technology has progressed significantly from early experiments in the 1940s. Current popular methods for 3D TV include stereoscopy using glasses to separate images for the left and right eyes. Holography offers the most realistic 3D effect by replicating the entire light field but requires immense computing power. Major players in the 3D TV market today include Samsung, Panasonic, and Sony, who offer large screen LCD and plasma models with support for 3D content from multiple sources.
3D television technology has progressed significantly from early experiments in the 1920s. Current 3D TV uses stereoscopy to display slightly different images for the left and right eyes, requiring the viewer to wear glasses. Alternative autostereoscopic displays aim to eliminate glasses but have limitations. True holography, which fully replicates light fields, has not been achieved for 3D TV due to the enormous data and bandwidth requirements. The document discusses the history and state of 3D display technologies as well as their applications beyond entertainment.
3D television technology has progressed significantly from early experiments in the 1940s. Current popular methods for 3D TV include stereoscopy using glasses to separate images for the left and right eyes. Holography offers the most realistic 3D effect by replicating the entire light field, but requires immense processing power. Major players in the 3D TV market today include Samsung, Panasonic, and Sony, who offer large-screen LCD and plasma models with support for 3D content from multiple sources. However, the ideal 3D display would eliminate issues like eye fatigue and the conflict between eye focus and convergence.
This ppt contains all the details of Stereoscopic imaging. It includes from history, introduction, its working technique, 3D viewers, 3D cameras, future scope, advantages, disadvantages. In all, its the complete stuff that can satisfy anyone.
Optimized and efficient deblurring through constraint conditional modellingnooriasukmaningtyas
Image deburring technique refers to restoring an image from the degraded version named blurred. Blurring can be caused due to various phenomena such as optical system, motion blur and other phenomena. Moreover, to deblur the image it is essential to know the blurring process characteristics and it is one of the difficult task. In past several deblurring algorithm have been proposed to approximate the kernel blur, however they lack the efficiency and expensive to be applied for the real world scenario. In this paper, we have proposed a CCM (constraint conditional model) to deblur the image; it learns the direct mapping from the degraded to the absolute clean image. Moreover, the main aim of CCM is to restore the image in its original form, the best advantage of CCM is that it provides handsome tradeoff between the image quality and efficiency. Moreover, CCM is evaluated on the three different standard datasets by considering the different performance metrics and through the comparison analysis observation has made that CCM approach outperforms the other techniques.
MODULE 2 computer vision part 2 depth estimationgarimajain959768
Depth estimation techniques use stereo vision or multiple camera views to extract depth information from 2D images. Stereo vision involves using two cameras to capture left and right images of a scene. The disparity between corresponding pixels is used to calculate depth. Key steps include camera calibration, image rectification, disparity calculation to find pixel matches between images, and triangulation to compute depth from pixel disparity and camera parameters. Multi-camera views provide enhanced coverage, improved depth perception, and redundancy by capturing different perspectives of a scene simultaneously.
Similar to VIRTUAL VIEWPOINT THREE-DIMENSIONAL PANORAMA (20)
artificial intelligence and data science contents.pptxGauravCar
What is artificial intelligence? Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the intellectual processes characteristic of humans, such as the ability to reason.
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Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
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Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
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Applications of artificial Intelligence in Mechanical Engineering.pdf
VIRTUAL VIEWPOINT THREE-DIMENSIONAL PANORAMA
1. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.6, December 2014
DOI : 10.5121/ijcseit.2014.4602 9
VIRTUAL VIEWPOINT THREE-DIMENSIONAL
PANORAMA
Abdulkadir Iyyaka Audu1
and Abdul Hamid Sadka2
Department of Electronic and Computer Engineering, Brunel University, London, United
Kingdom
ABSTRACT
Conventional panoramic images are known to provide for an enhanced field of view in which the scene
always has a fixed appearance. The idea presented in this paper focuses on the use of the concept of virtual
viewpoint creation to generate different panoramic images of the same scene with three-dimensional
component. Three-dimensional effect in a resultant panorama is realized by superimposing a stereo-pair of
panoramic images.
KEYWORDS
Binocular vision, Panoramic images, Cylindrical warping, 3D depth effect, Anaglyph.
1. INTRODUCTION
The replication of natural viewing experience derived from television through the addition of
depth component has been widely studied [1]. In particular the experience of “immersion” in a
three- dimensional (3D) environment has gone through a dynamic growth [2]. In the words of [3],
“In face-to-face meetings, we each change our location and direction of gaze so naturally that we
hardly give it a thought. In addition, when someone is looking at us, not only do we see that
person looking at us, but everyone else can observe that person looking at us from his or her own
point of view. It has been shown that mutual gaze enhances human communication”. This is
depicted in Figure 1.
(a) (b)
Figure 1: Examples of live 3D scene depicted.
2. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.6, December 2014
10
The provision of depth perception of images and video in panoramic television is now an active
and relevant research topic. The knowledge of stereoscopy is crucial in this regard. It is widely
understood that a change of viewpoint with respect to an observed object provides either a slightly
or considerably different view of the object. This effect which is attributable to the fact that
humans have two eyes and see through perspective projection has been extensively studied in
both human vision system (HVS) and machine vision system (MVS). Also, many complex visual
tasks, such as reading, detecting camouflaged objects, and eye-hand coordination are also
performed more effectively with two eyes than with one, even when the visual display contains
no depth [4].
The degree of perceived (3D) realism and enhanced field of view (FOV) are two important factors
in vision analysis. In the work of [5], it is observed that retriever of information on the 3D
structure and distance of a scene, from a stereo pair of images has become a popular concept in
computer vision. In some medical relevant applications robustness, accuracy, and real-time
capability are of utmost importance.
A refined analysis has indicated that emerging areas of application in multimedia, with
extraordinary standing such as three-dimensional television (3DTV) and free-view television
(FVT) are some of the driving factors for this development [6]. Multi-view video is one of the
enabling technologies which have recently brought 3DTV and FVT to prominence [7, 8]. In spite
of the enormous advantages associated with 3DTV and FVT, [9]. has noted the bandwidth
requirement issue, which is critical and challenging for transmitting additional data to render the
auxiliary view(s).
Enhanced FOV is the main motivation factor of [10]. It is emphasized that for any FOV
enhancement to be achieved, the entire imaging system must have a single effective viewpoint to
enable the generation of pure perspective images from a sensed image. The single viewpoint
constraint is satisfied by incorporating reflecting mirrors into the conventional imaging system.
In this work, generation of (3D) content from a stereo pair of panoramic views of a scene is
proposed. In the view of [11], the following advantages cannot be divorced from stereoscopic
view. Depth perception relative to the display surface; spatial localization, allowing concentration
on different depth planes; perception of structure in visually complex scenes; improved
perception of surface curvature; improved motion judgment; improved perception of surface
material type. These benefits give stereoscopic displays improved representation capabilities that
allow the user a better understanding or appreciation of the visual information presented.
A panoramic image has the established reputation and capability to provide a 360 degree view of
a scene. It is usually obtained by stitching image samples together. It has been widely investigated
in the work of [12, 13, 14]. It is also a variant of image-based rendering that allows 3D scenes and
objects to be visualized in a realistic way without full 3D model reconstruction. The concept of
panoramic image stitching stems from the fundamental deficit in the narrow field of view (FOV)
of most compact cameras as depicted in Figure 2.
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Figure 2: A compact camera image formation process.
The main object of this work is to construct a panoramic image with depth perception. This will
be in line with the increasing possibility of panoramic television.
Section II discusses basic concepts of vision, 3D effect, and panoramic view. The focus in section
III is the strategy of implementation. Experimental results and discussion are presented in section
IV. Conclusion on the proposition is drawn in V.
2. THREE-DIMENSIONAL CONTENT
2.1. Binocular Vision and Stereoscopy
Binocular vision involves the use of two eyes or optical devices for the acquisition of both the
optical and geometric property of a scene. It is thought to provide for increased field of view,
binocular summation which is the enhancement in the detection of faint objects, and the use of
stereoscopic distance or disparity to perceive a scene in 3D and the distance of an object [15]. The
amazing effect of significant proportion is the composition of a single image using the single
individual image of each eye. This is generally referred to as binocular fusion. The superposition
of a pair of images to create depth illusion is known as anaglyph.
In [16], it is believed that parallax, movement parallax, accommodation, convergence, re-
membered geometry of an object and linear perspective, occlusion, shading, and resolution
constitute both physiological and psychological factors, which determine the level of 3D effect
we observe as humans. However, parallax and convergence are the most needed factors for
anyone to perceive 3D effect. With accommodation, neurophysiological process varies the radius
of curvature of the eye lens to focus the image on the retina. However, with convergence, the
continuous movement of the eye ball causes certain angle which decreases with distance to be
subtended between the visual axis and optical axis of each eye. This is perhaps linked to the
availability of neural algorithm which plays a prominent role in the binarization and manipulation
of information the eyes receive.
2.2. Anaglyph and Synthetic 3D Effect
At man-made level, the singleness of vision created by neural algorithm in humans is reversed.
There are several stereoscopic display methods that can be used to generate 3D effect. These
include lenticular sheet, integral photography, horse blinder barrier, parallax barrier, varifocal
mirror, volumetric methods, head mounted display, time sharing method, anaglyph, Brewster’s
stereoscope, Wheatstone’s stereoscope, and 3D movies. From either the projection or interception
type of display, one of the two slightly different images of the same object captured with two
similar cameras separated by a certain stereoscopic distance is presented to each eye alternately
through a filter glass. This concept is demonstrated in Figure 3, [16].
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Figure 3: Parallax effect. (a) Object. (b) Projected views of the object. (c) Transposed images.
Whatever display type is used, comfortable view in terms of reduced eye strain or absence of
double images from excessive perceived depth is highly required. In [8], it is stated that the
mentioned requirement is a function of stereoscopic camera parameters. It is further mentioned
that a stereoscopic camera system with parallel axes should be used to avoid the vertical image
disparity generated by systems that verge the camera axes. This is because for a parallel camera
system, points at infinity have zero disparity and are perceived by the viewer in the plane of the
target display. To ensure that corresponding points in the left and right images, at other distances
from the viewer, are perceived in the screen plane, the images must be adjusted during or after
capture. All these explain the difficulty in producing comfortable images which are often only
produced after repeated trial and error. Some common challenges are highlighted in Figure, [17].
5. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.6, December 2014
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(a) (b)
(c) (d)
(e) (f)
(g) (h)
Figure 4: Causes of 3D discomfort: (a) the distance between the cameras is not adequate, (b) cameras were
converged on the wrong point, or one eye was excessively horizontally shifted, (c) lens mismatch, (d) poor
manual control on focus distance, and autofocus modes may disagree on the subject distance, (e) keystone
appears when the optical axes are not parallel, due to convergence or, less often, strong vertical
misalignment, (f) image rotation appears when the camera’s optical axis is rotated along the Z axis, (g) both
left and right images are shot without paying great attention to time synchronization, (h) one camera is most
likely pointing up or down, or a zoom is off-axis.
2.3. Anaglyph Computation
In Figure 5, two similar cameras with a focal length of f and having a stereoscopic distance of b
between them are used to acquire a world point (X, Y, Z). The relationship between the world
point and the respective corresponding points ሺݔோ, ݕோሻ in the right image and ሺݔ, ݕሻ in the left is
expressed as
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௫ಽ
=
ା
್
మ
௭
,
௫ೃ
=
ି
್
మ
,
௬ಽ
=
௬ೃ
=
(1)
The disparity D between corresponding right and left image points is expressed in (2). The
reciprocal of D gives the depth of the world point with respect to the vertical plane contain plane
containing the cameras and it decreases with stereoscopic distance. It is also important to note
from (1) that disparity is directly proportional to the product of camera focal length and
stereoscopic distance, and inversely proportional to the depth D.
ܦ = ݔ − ݔோ (2)
Figure 5: A compact camera image formation process.
It is now been proven that a convincing and comfortable viewing experience can be realized not
by maintaining a certain angular disparity as earlier suggested by human factor studies [18] but by
compression of scene depth. In [11], this idea is depicted as shown in Figure 6.
Figure 6: Screen compression: the scene depth (bottom) is compressed (top).
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In the simplified case of a static viewer analyzed in [8], camera separation b can be computed
using the relation (3). Where Z is the distance of the cameras from the ‘virtual’ display (zero-
Disparity-Plane) in the scene, N is the distance from the cameras to the closest visible points in
the scene, dN is the disparity, on the display, of objects appearing at the limit N
ܾ =
ଶᇲ ୲ୟ୬ቀ
ഇ
మ
ቁௗಿேᇲ
ௐሺᇲିேᇲሻାௗಿேᇲ (3)
The following five types of anaglyph are well known in computer vision. True anaglyphs, colour
anaglyphs, grey anaglyphs, half colour anaglyphs, and optimized anaglyphs. According to [19],
colour is the general name for all sensations arising from the activity of the retina of the eye and
its attached nervous mechanisms, this activity being, in nearly every case in the normal
individual, a specific response to radiant energy of certain wavelengths and intensities. This
understanding can be explored to seek a mathematical representation of anaglyph. In terms of
implementation, colour and grey anaglyphs are usually composed based on the mathematics
expressed in (4) and (5) respectively. Ar, Ag, Ab are the colour components of the anaglyph
generated from panoramic images 1 and 2 with r, g, b colour components.
A୰
A
Aୠ
=
1 0 0
0 0 0
0 0 0
൩
1୰
1
1ୠ
+
0 0 0
0 1 0
0 0 1
൩
2୰
2
2ୠ
(4)
A୰
A
Aୠ
=
0.299 0.587 0.114
0 0 0
0 0 0
൩
1୰
1
1ୠ
+
0 0 0
0.299 0.587 0.114
0.299 0.587 0.114
൩
2୰
2
2ୠ
(5)
The limited field of view of conventional imaging devices such as pinhole camera is a problem
which is familiar to computer vision researchers and diagnosed by [20, 21]. It is pointed out that
while surveillance, teleconferencing, and model acquisition for virtual reality constitute a driving
force for an increased field of view, there are several other application areas which are
strategically positioned to take advantage of field of view enhancement.
Catadioptric image formation process is widely used for enhancing the field of view of imaging
devices. However, image mosaic is favoured in some situations since catadioptric image
formation has associated problems of sensor resolution and focusing. Furthermore, in the idea of
gradient domain approach presented in [22], of image stitching, the similarity of the sample
images and visibility of the seam constitute the cost functions to be optimized. This eventually
suppresses both photometric inconsistencies and geometric misalignments between the stitched
images.
The method for the generation of panorama falls into two categories namely direct and feature-
based methods. It is clear from [23] that accuracy of image registration and closed initialization
are the main differences between the two. Feature-based method is considered in this work, since
panoramic view generation is one of the image-based rendering methods and features can only be
obtained from reference images.
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Of course, the image formation model based on Snell’s law developed by [21] is known and well
appreciated. In this model, one object point P 0 is traceable to obtain two image coordinates
ሾ,ݑ ݒሿ்
and ሾݑᇱ
, ݒᇱሿ்
on a CCD camera by use of skew ray tracing and taking a single-camera two
panoramic views. This camera type is yet to be readily available in the market. In this regard, the
use of two separate cameras on a single tripod separated by certain stereoscopic distance is
inevitable.
In image mosaicking, the image is first mapped onto the surface of a cylinder, sphere, cube and
then the curved surface is unrolled. A method to estimate surface projection is well documented
in the work of [14]. Cylindrical warping, [24], can be obtained using either forward or inverse
warping as depicted in Figure 7. In forward warping: from image coordinate (x, y), the projected
coordinates on the cylinder ሺݔᇱ
, ݕᇱሻ are given in (6) and (7). Where S is the scaling factor and ݂
equals lens focal length in pixels.
ݔᇱ
= ܵߠ = ܵ tan−1
ቀ
௫
ቁ (6)
ݕᇱ
= ܵℎ = ܵ ൬
௬
ඥሺ௫మାమሻ
൰ (7)
Figure 7: Cylindrical projection.
For inverse warping: inverse mapping from cylindrical coordinates to image (x, y) is expressed in
(8) and (9).
ݔ = ݂ tan ߠ = ݂ tan ቀ
௫ᇲ
ௌ
ቁ (8)
ݕ = ℎඥሺݔଶ + ݂ଶሻ = ݂ ቀ
௬ᇲ
ௌ
ቁ sec ቀ
௫ᇲ
ௌ
ቁ (9)
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3. IMPLEMENTATION STRATEGY
The implementation of this work is carried out in two stages as shown in Figure 8. First is the
generation of two separate panoramic views of a scene. Second is the anaglyph composition.
Figure 8: Block diagram for generating 3D effect from two panoramic view.
3.1. Generation of Panoramic Image
• The first crucial step in the generation of any panoramic view is the acquisition of image
samples of a scene through 360 degrees camera panning. Several images capture different
portions of the same scene, with an overlap region viewed in any two images. A path
description of each image location is then contained in a text file.
• In this work, a cylinder is used as the projection surface. This allows for an 180 x 360o
field of view enhancement. This step is then followed by correction of radial distortion
associated with image. Two types of radial distortion can be corrected: barrel and
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pincushion. In "barrel distortion", image magnification decreases with distance from the
optical axis. The apparent effect is that of an image which has been mapped around a
sphere (or barrel). In pincushion distortion, image magnification increases with the
distance from the optical axis. The visible effect is that lines that do not go through the
center of the image are bowed inwards, towards the centre of the image, like a
pincushion. Brown’s (1972) extension of Magill’s formulation for variation of radial
distortion with focusing still remain potentially attractive. This is in spite of the re-
verification by [25, 26, 27], with data of much higher precision than the previous
investigations. Brown’s distortion. This is expressed in (10) and (11). (xd, yd) describes
the coordinates of the distorted image while (xu, yu) is for the undistorted.
ݔௗ = ݔ௨൫1 + ሺ݇ଵݎଶሻ + ሺ݇ଶݎସሻ൯ (10)
ݕௗ = ݕ௨൫1 + ሺ݇ଵݎଶሻ + ሺ݇ଶݎସሻ൯ (11)
• Fundamentally, image registration involves the establishment of a motion model which
allows for proper integration of useful information from multiple images of the same
scene taken at different times, from different viewpoints and/or by different sensors.
Depending on the area of application, image registration can be either multi-temporal
analysis (different time), multi-view analysis (different viewpoints), scene to model
registration (images of a scene and its model are registered), and multimodal analysis
(different sensors are used in image acquisition).
• It is well established in literature that irrespective of application area, an image
registration is usually implemented under five steps namely: feature detection in which
the descriptive image regions called feature points are detected, feature extraction, feature
matching, motion model estimation, and image re-sampling and transformation. Scale
invariant feature transform (SIFT), [28][20], is used for detection and extraction of a
much larger number of features from the images, which reduces the contribution of the
errors caused by these local variations in the average error of all feature matching errors.
It is characterized by detection and localization of key-points in different scale space
images, followed by the assignment of an orientation to each key-point using local image
gradients. Then a key-point descriptor is assembled from the local gradient values around
each key-point using orientation histograms.
• The accuracy of panoramic mosaic to a large extent is dependent on the image matching
technique employed in the establishment of correspondence between one or several
images and a reference. Correspondence between any two images is established using
feature- based matching. The features common under geometric constraints to the two
images called inliers serve as a prerequisite for the computation of projective matrix and
subsequently the motion model. The inliers are computed using an algorithm for robust
fitting of models in the presence of many data outliers. The composition of the motion
model is such that it allows an image to be transformed with respect to another which is
considered to be the reference. The obvious consequence of this process is that the
transformed image can then be stitched to the reference image at the proper coordinate
points.
• Pyramid blending technique is implemented to allow for a smooth transition from one
image to the other across the transition boundary. Pyramid blending involves the
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combination of different frequency bands with different alpha masks. Lower frequencies
are mixed over a wide region, and fine details are mixed in a narrow region. This
produces gradual transition in lower frequencies, while reducing edge duplications in
textured regions.
3.2. Anaglyph Composition
The second stage at broad level is the anaglyph composition. Two colour panoramic views left (1)
and right (2) are used to construct colour anaglyph.
Trimming adjustment is also used to vary the horizontal disparity until a comfortable and natural
looking image is obtained. In the case of colour anaglyph, the RGB components are maintained
even after the coding operation.
4. SIMULATION RESULTS AND DISCUSSION
The results and appropriate discussion about this work is presented as follow. Each image sample
is acquired using a compact digital camera at a resolution of 2464 × 1632.
4.1. Results
(a)
(b)
(c)
(d)
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(e)
(f)
Figure 9: 3D effect due to stereo panoramic image. (a) and (b) are left and right images. (c), (d), (e), and (f)
are images with different 3D effects.
(a)
(b)
(c)
(d)
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(e)
(f)
Figure 10: 3D effect due to stereo panoramic image. (a) and (b) are left and right images. (c),(d), (e), and (f)
are images with different 3D effects.
(a)
(b)
(c)
(d)
(e)
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(f)
Figure 11: 3D effect due to stereo panoramic image. (a) and (b) are left and right images. (c),(d), (e), and (f)
are images with different 3D effects.
(a)
(b)
(c)
(d)
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Figure 12: Outdoor scenes: (a) left view and (b) right view of first scene. The second scene also has (c) and
(d) as left and right views respectively.
4.2. Discussion
All figures, tables, Two sets of image samples at a resolution of 2464 × 1632 are acquired using
two compact digital cameras (Nikkon D7000) mounted on a single tripod. Each set contains thirty
six images. Image acquisition was made with stereoscopic distance of 130mm, 140mm, 150mm,
and 160mm.
Thirty eight sample images have been used for each of the constructed panoramic views with the
first and last images being repeated. One important observation is that, in the panoramic views of
Figure 9 through to Figure 11, the observed perspective projection is different for similar objects
of the same physical size located at almost the same point in the scene. This is due to change in
viewpoint. Also the 3D effect which is observed through a pair of anaglyph glasses increases
from (c) through to (f) in the just mentioned figures. What can be noticed is the pop out effect
from the screen.
Also two other panoramic image pairs of out-door scenes are presented in Figure 12. 3D effects
could equally be generated from each pair.
5. CONCLUSION
The generation of 3D effect from two panoramic views whose image samples are obtained from
two synchronized cameras, has been demonstrated. Acquisition of image samples is carried out in
both indoor and outdoor environments. Little or considerable vegetation has been used as a
criteria for the choice of outdoor environment in this work. It is important to note that the quality
of 3D effect largely depends on how well the image samples have been well stitched. The
subjective assessment based on the viewing experience of a group of people confirms that the
resultant depth quality is good and does not cause much eye strain.
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