Stereo Vision (Computer Vision)

Visual impairment and blindness caused by infectious diseases has been greatly reduced, but increasing numbers of people are at risk of age-related visual impairment. Visual information is the basis for most navigational tasks, so visually impaired individuals are at disadvantage because appropriate information about the surrounding environment is not available. With the recent advances in inclusive technology it is possible to extend the support given to people with visual impairment during their mobility. In this context we propose a system, named SmartVision, whose global objective is to give blind users the ability to move around in unfamiliar environments, whether indoor or outdoor, through a user friendly interface. This paper is focused mainly in the development of the computer vision module of the SmartVision system.

In this work, we proposed a novel depth adaptive tone mapping scheme for stereo HDR imaging and 3D display. We are interested in the case where different exposures are taken from different viewpoints. The scheme employed a new depth-adaptive cross-trilateral filter (DA-CTF) for recovering High Dynamic Range (HDR) images from multiple Low Dynamic Range (LDR) images captured at different exposure levels. Explicitly leveraging additional depth information in the tone mapping operation correctly identify global contrast change and detail visibility change by preserving the edges and reducing halo artifacts in the synthesized 3D views by depth-image-based rendering (DIBR) procedure. The experiments show that the proposed DA-CTF and DIBR scheme outper-forms state-of-the-art operators in the enhanced depiction of tone mapped HDR stereo images on LDR displays.

We would like to invite you to join this exciting new project as a chapter contributor. Since this is a textbook, a great deal of this chapter entails a survey on the topic under the paradigm of cyber-physical systems, what can be done onboard and remotely, the distributed nature of the system and some exercises on futurology (anticipating trends can shed some light on upcoming designs). IET will bring great visibility to your work. You are welcome to suggest another topic/chapter title if you feel it would be more suitable. Each chapter should be around 20-25 pages each and can be submitted as a Word or Latex File. The IET will send you additional information (formatting, permission form, etc.) with the contributor's agreement once you have agreed to contribute to the book. Visit http:// www.theiet.org/resources/author-hub/books/index.cfm to get all information you need as a contributor to an IET research-level book. Each book is expected to have a total number of 500 printed pages (based on approximately 550 words per page with a 20% allowance for figures and tables). We have included a tentative schedule and list of topics below. If this is something you would consider, please send me the title of your chapter, a short description/abstract of the chapter content, and your full contact details. We will expect original content and new results for this book. You can, of course, reuse published material but the percentage of material reuse for the chapter should be less than 40%. The IET will run a piracy software on the full manuscript to control that you are including original material and will reject chapters who contain a large amount of already-published material so please do take this into consideration.

It is well known that this soiling can reduce the generation efficiency in PV system. In some case according to the literature of loss of energy production in photovoltaic systems can reach up to 50%. In the industry there are various types of cleaning robots, they can substitute the human action, reducing cleaning cost, be used in places where access is difficult, and increasing significantly the gain of the systems. In this paper we present an application of computer vision method for soiling recognition in photovoltaic modules for autonomous cleaning robots. Our method extends classic CV algorithm such Region Growing and the Hough. Additionally, we adopt a pre-processing technique based on Top Hat and Edge detection filters. We have performed a set of experiments to test and validate this method. The article concludes that the developed method can bring more intelligence to photovoltaic cleaning robots.

International Journal of Computer Vision and machine learning (IJCVML) is an open access, peer-reviewed journal that publishes articles which contribute new results in all areas of the advanced vision computing. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding advances in vision computing and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of vision computing.

The report focuses on two main calibration tools, i.e., single camera and setreo vision system calibration. The goal of the report is to show how one of the most known techniques for camera calibration can be used to calibrate any given camera system. In the calibration method, one planar pattern is shown in different orientations to the target camera and an image database is acquired. The Camera Calibration toolbox in MATLAB [10] is followed as a main calibration procedure. Moreover, the optional part of the work which requests calibration of the stereo vision system is carried out. For this purpose, two cameras of different smartphones are used and calibrated. the intrinsic, exterinsic, error for each calbiration are reported at the end. Index Terms-camera calibration, stereo vision system, intrinsic and extrinsic parameters, error, checkerboard

A complete manual of Perspective from 0 to 6 vanishing point, including the curvilinear perspective.
Master the curvilinear perspective with four, five and six vanishing point.
Sketch  futuristic cars or the ultimate mp3 player by freehand technique.
Have fun with anamorphic projections and stereo drawings for a 3D effects.
Circles, shadows, people, reflections, and much more.
There is also a 5 languages Dictionary and Terminology page. (Italiano, English, Español, Français, Deutsch).
The book is in Italian.

The Optical Marking Recognition (OMR), or optical mark reading, is an automated data input process of capturing presence or absence of marked data (crosses, ticks and filled regions) on printed papers such as multiple choice examinations (MCQs) and surveys. Usually, a specific OMR machine is used to recognize the correctly marked data on a printed paper, which is highly expensive and requires a specialized technician to operate the machine accurately. This research proposes an accurate, timely and cost effective OMR sheet evaluation system based on a low priced web camera that can evaluate any format of MCQ paper efficiently. Firstly the selected region with all correct answers is marked on the printed paper separated manually and will be used as a template image in the matching process to extract the answered region of the student answer script. Then the cropped region of the answer sheet is matched with the template image to recognize the answers marked as correct or incorrect. Results obtain an accuracy of 97.6% over three different formats of MCQ papers.

The objective of this paper is to review the Stereo-Triangulation in computer vision, investigating the reconstruction of three-dimensional data corresponding using the 2-D images in a situation where images contain noise. Finally four optimization methods were implementation for Triangulation simulation in the noisy condition. The cameras were modelled using Peter Corke's MVTB toolbox in MATLAB and Gaussian noise was used to simulate noisy condition. Comparison of the result for four selected optimization methods, i.e., poly-abs, lindstrom, sampson and mid-point shows that poly-abs performs better in practice and create less error.

Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, and security and surveillance. The aim of this book, 'Deep Learning for Image Processing Applications', is to offer concepts from these two areas in the same platform, and the book brings together the shared ideas of professionals from academia and research about problems and solutions relating to the multifaceted aspects of the two disciplines. The first chapter provides an introduction to deep learning, and serves as the basis for much of what follows in the subsequent chapters, which cover subjects including: the application of deep neural networks for image classification; hand gesture recognition in robotics; deep learning techniques for image retrieval; disease detection using deep learning techniques; and the comparative analysis of deep data and big data. The book will be of interest to all those whose work involves the use of deep learning and image processing techniques

Scope of the book:
This book focusses on the technical concepts of deep learning and its associated branch Neural Networks for the various dimensions of image processing applications. The proposed volume intends to bring together researchers to report the latest results or progress in the development of the above-mentioned areas. Since there is a deficit of books on this specific subject matter, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings.
Topics of Interest:
This book solicits contributions, which include the fundamentals in the field of Deep Artificial Neural Networks and Image Processing supported by case studies and practical examples. Each chapter is expected to be self-contained and to cover an in-depth analysis of real life applications of neural networks to image analysis.

This paper presents a method of camera calibration of stereo pair for stereo vision application. The method is using Jean-Yves Bouguet tool which produces the intrinsic and extrinsic parameters of stereo pair. The data of calibration will be used in image rectification between two images. Then the rectified image will go through the block matching process. The block matching technique is briefly described with the performance of its output. The disparity mapping is generated by the algorithm with the reference to the left image coordinate. The algorithm uses Sum of Absolute Differences (SAD) which is developed using Matlab software.

Patch-based  stereo  is  nowadays  a  commonly  used image-based technique  for  dense  3D  reconstruction  in  large  scale  multi-view applications. The typical steps of such a pipeline can be summarized in stereo pair selection, depth map computation, depth map refinement and, finally, fusion in order to generate a complete and accurate representation of the scene in 3D. In this study, we aim to support the standard dense 3D reconstruction of scenes as implemented in the open source library OpenMVS by using semantic priors. To this end, during the depth map fusion step, along with the depth consistency check between depth maps of neighbouring views referring to the same part of the 3D scene, we impose extra semantic constraints in order to remove possible errors and selectively obtain segmented point clouds per label, boosting  automation towards this direction. I n order to reassure semantic coherence between neighbouring views, additional semantic criterions can be considered, aiming to elim inate mismatches of pixels belonging in different classes.

These articles on 3DTV and 3D movies were written over the last two decades of the 43 year period since I began. They are illustrated with original photos and historical materials resulting from thousands of hours researching the technical and patent literature and attending and exhibiting at trade shows. I decided to publish them in a book as they have only existed in scattered locations and they have proven quite popular when I recently posted some of them on the net. They present information and viewpoints difficult or impossible to find that nicely supplement what is available elsewhere.

This book has now been published in a revised version in ebook and printed versions  https://www.amazon.com/3DTV-3D-Movie-Technology-1996-2017-ebook/dp/B0723GVVJ9 .

As with all sites, the archives of 3DTV Corporation may be viewed on the wayback machine at https://web.archive.org/web/*/http://3dmagic.com and it’s mirror https://web.archive.org/web/*/http://3dtv.jp

These articles on 3DTV and 3D movies were written over the last two decades of the 44year period since I began. They are illustrated with original photos and historical materials resulting from thousands of hours researching the technical and patent literature and attending and exhibiting at trade shows. I decided to publish them in a book as they have only existed in scattered locations and they have proven quite popular when I recently posted some of them on the net. They present information and viewpoints difficult or impossible to find that nicely supplement what is available elsewhere.

The comprehensive coverage of various trade shows held at the peak of the 3D frenzy (ca 2009-11) are a unique record of what was actually available in the market place at major international shows. To attend one of them would cost the average participant over $1000 and a week’s time, with many hours a day walking the floor, fighting the crowds and exhaustion, and very few would see or understand most of what was on display. This was easier for me as I had already spent 36 years studying 3D full time. I exerted the most effort at NAB (the National Association of Broadcasters) where I trudged the aisles about 8 hours a day for 5 days visiting most of the 3D relevant booths twice, and then spent several weeks reading and researching to put them into context. The patent and technical literature searches however occupied four decades. I also include several practical articles on making and viewing 3D video that include numerous tips not present in the many books and articles I have seen. I make no attempt to repeat the material in the many excellent books and countless articles that have appeared recently. Those who want a fairly comprehensive coverage of 3D technology should get the SPIE CD with many hundreds of articles from 1977 to 2009 ISBN-10: 0819476595 and subsequent proceedings, and of course for the diligent there is no substitute for the patent literature.

As I comment in several places, though thousands (or millions) have contributed to the technology that gave rise to the rebirth of 3D films and television, if I had to pick out just two, then I think Larry Hornbeck of Texas Instruments, who invented the DLP micromirror technology used for projection, and Brian Critchley of projector maker Digital Projection, who took the lead in researching and developing it into a workable cinema projector, deserve top honors. I continue to sell 3D hardware as a hobby and greatly enjoy hunting down obscure 3D films on the net (many of them never released theatrically in 3D and only distributed on 3D blu-ray in one part of the world, and so only seen in 3D by a tiny minority of the viewing public).

The goal of the project" SmartVision: active vision for the blind" is to develop a small and portable but intelligent and reliable system for assisting the blind and visually impaired while navigating autonomously, both outdoor and indoor. In this paper we present an overview of the prototype, design issues, and its different modules which integrate a GIS with GPS, Wi-Fi, RFID tags and computer vision. The prototype addresses global navigation by following known landmarks, local navigation with path tracking and obstacle avoidance, and object ...

Most stereo algorithms assume images to be epipolar aligned. There are two ways of achieving this (i) physically aligning the cameras or (ii) rectifying the stereo images after capturing them. For real-time or fixed stereo head applications aligning the cameras is preferable because rectifying the stereo images would require precious computational resources and once set the cameras remain in alignment. For applications involving mobility of stereo head, like in robots, it is preferable to rectify images using software because the alignment of cameras could change with time. In this paper we use affine like transform to rectify stereo images and demonstrate its usefulness in producing better disparity estimates and show it can be used to capture stereo images from a single camera.Most stereo algorithms assume images to be epipolar aligned. There are two ways of achieving this (i) physically aligning the cameras or (ii) rectifying the stereo images after capturing them. For real-time or fixed stereo head applications aligning the cameras is preferable because rectifying the stereo images would require precious computational resources and once set the cameras remain in alignment. For applications involving mobility of stereo head, like in robots, it is preferable to rectify images using software because the alignment of cameras could change with time. In this paper we use affine like transform to rectify stereo images and demonstrate its usefulness in producing better disparity estimates and show it can be used to capture stereo images from a single camera.

Anyone shooting 3D is immediately confronted with the problem of stereo camera geometry—how to align the cameras for best results.  This looks like it should be the easiest part of the entire project but in fact it’s by far the hardest.  Just aligning the cams perfectly in all 3 axes and locking them down is tough and keeping them aligned when changing interaxial, convergence or zoom is extremely hard.  There is very little in the way of comprehensive reviews of this subject in the literature. Some may be surprised to learn that these problems are not new, nor are they unique to 3D video and photography.  In addition to attention from stereographers for over 150 years, they have been the subject of intensive research in the fields of photogrammetry going back well over 100 years, and more recently in computer vision.  Every book in these arenas has extensive discussions on multiple camera geometry and essentially the entire texts revolve around the problems of camera registration and image rectification for human viewing and/or computer image understanding.  Algorithmic transforms for producing rectified images from single moving cameras, polydioptric (plenoptic or multiple image single lens cameras) or multiple cameras take up large sections of these books and thousands of papers, which blend into the literatures of robotics, machine vision, artificial intelligence, virtual reality, telepresence and every aspect of 3D imaging.  Here I provide a cursory review with a few pertinent references.

This article has now been published in a revised version in ebook and printed versions  https://www.amazon.com/3DTV-3D-Movie-Technology-1996-2017-ebook/dp/B0723GVVJ9 .

As with all sites, the archives of 3DTV Corporation may be viewed on the wayback machine at https://web.archive.org/web/*/http://3dmagic.com and it’s mirror https://web.archive.org/web/*/http://3dtv.jp

The problem of recursively approximating motion resulting from the Optical Flow (OF) in video thru Total Least Squares (TLS) techniques is addressed. TLS method solves an inconsistent system Gu=z , with G and z in error due to temporal/spatial derivatives, and nonlinearity, while the Ordinary Least Squares (OLS) model has noise only in z. Sources of difficulty involve the non-stationarity of the field, the ill-posedness, and the existence of noise in the data. Three ways of applying the TLS with different noise conjectures to the end problem are observed. First, the classical TLS (cTLS) is introduced, where the entries of the error matrices of each row of the augmented matrix [G;z] have zero mean and the same standard deviation. Next, the Generalized Total Least Squares (GTLS) is defined to provide a more stable solution, but it still has some problems. The Generalized Scaled TLS (GSTLS) has G and z tainted by different sources of additive zero-mean Gaussian noise and scaling [G;z] by nonsingular D and E, that is, D[G;z]E makes the errors iid with zero mean and a diagonal covariance matrix. The scaling is computed from some knowledge on the error distribution to improve the GTLS estimate. For moderate levels of additive noise, GSTLS outperforms the OLS, and the GTLS approaches. Although any TLS variant requires more computations than the OLS, it is still applicable with proper scaling of the data matrix.

Humanoid robots such as DLR’s Justin were designed to interact with unknown environ-
ments and cooperate with humans. To ensure safety and mobility they are built with
light-weight structures and flexible mechanical components. This light-weight design en-
ables the robot to achieve a compliant behavior of the arm kinematic chain, with the
draw-back of having a low positioning accuracy at the TCP (Tool-Center-Point) end-pose
of the hand. Torque sensors are used to approximate the deflections of the joints and
compensate the TCP end-pose errors. However, this approximation is insufficient due to
remaining unidentified errors and flexibilities in the joints and links. The identification of
a maximum TCP end-pose error is essential for object manipulation and path planning.
This thesis proposes a verification routine for the identification of the maximum bounds
of the TCP end-pose errors by using the on-board stereo vision system. The error identi-
fication is based on the pose estimation of 3D point clouds of Justin’s hand using state-of-
the-art 3D registration techniques.
A model of the hand is required for pose estimation. The hand’s CAD (Computer-Aided-
Design) model does not accurately reflect the data observed by the stereo vision system,
therefore we generate models of the hand by registering multiple 3D point clouds. Be-
cause the hand is a self-occluding object a full model is not achievable. Partial models are
generated by creating subsets of overlapping point clouds. We proposed a method for the
rejection of non-overlapping point clouds based on a statistical analysis of the depth values.
The partial models are created by applying an extended metaview registration method to
the remaining subset of point clouds.
The registration of a random point cloud of the hand to the model generates an estimate
of the TCP end-pose. This estimate is compared to the measured TCP end-pose obtained
by computing the forward kinematics of the arm using the joint angle measurements. The
verification routine consists in repeating this procedure with N -random poses. The bounds
of the TCP end-pose errors are identified as the maximum translational and rotational er-
ror from the set of random poses.
To evaluate the errors identified by using 3D registration, we implemented a marker-based
pose estimation method with the ARTrack IR Optical tracking system. This method re-
quired a robust calibration of tracking targets to Justin’s head and hands. The errors
estimated by using this tracking system are considered as the ground truth. Experimental
results showed that the estimated errors by using 3D registration are consistent with this
ground truth. Therefore, our proposed verification routine is suitable for the bound iden-
tification of Justin’s TCP end-pose errors. The identified bounds can be used to adjust
the obstacle clearance in path planning techniques. Unexpected collisions with the envi-
ronment can be prevented by setting this clearance to a value higher than the maximum
bound of the TCP end-pose errors.

Progress in image sensors and computation power has fueled studies to improve acquisition, processing, and analysis of 3D streams along with 3D scenes/objects reconstruction. The role of motion compensation/ motion estimation (MCME) in 3D TV from end-to-end user is investigated in this chapter. Motion vectors (MVs) are closely related to the concept of disparities, and they can help improving dynamic scene acquisition, content creation, 2D to 3D conversion, compression coding, decompression/decoding, scene rendering, error concealment, virtual/augmented reality handling, intelligent content retrieval, and displaying. Although there are different 3D shape extraction methods, this chapter focuses mostly on shape-from-motion (SfM) techniques due to their relevance to 3D TV. SfM extraction can restore 3D shape information from a single camera data.

This paper describes a real-time feature-based stereo SLAM system that is robust and accurate in a wide variety of conditions-indoors, outdoors, with dynamic objects, changing light conditions, fast robot motions and large-scale loops. Our system follows a parallel-tracking-and-mapping strategy: a tracking thread estimates the camera pose at frame rate; and a mapping thread updates a keyframe-based map at a lower frequency. The stereo constraints of our system allow a robust initialization-avoiding the well-known bootstrapping problem in monocular systems-and the recovery of the real scale. Both aspects are essential for its practical use in real robotic systems that interact with the physical world. In this paper we provide the implementation details, an exhaustive evaluation of the system in public datasets and a comparison of most state-of-the-art feature detectors and descriptors on the presented system. For the benefit of the community, its code for ROS (Robot Operating System) has been released.

This paper reports the modifications involved in preparing two commercial Ocean-Server AUV systems for simultaneous localization and mapping (SLAM) research at the University of Michigan (UMich). The UMich Perceptual Robotics Laboratory (PeRL) upgraded the vehicles with additional navigation and perceptual sensors including 12-bit stereo down-looking Prosilica cameras, a Teledyne 600 kHz RDI Explorer DVL for 3-axis bottom-lock velocity measurements, a KVH single-axis fiber-optic gyroscope for yaw rate, and a WHOI Micromodem for communication, along with other sensor packages discussed forthwith. To accommodate the additional sensor payload, a new Delrin nose cone was designed and fabricated. Additional 32bit embedded CPU hardware was added for data-logging, realtime control, and in-situ real-time SLAM algorithm testing and validation. Details of the design modification, and related research enabled by this integration effort, are discussed herein.

— The camera model has two fundamental modeling errors. The internal camera model needs a full perspective off squareness correction of the sensor plane, and the Bayer pattern recovery interferes with chromatic distortion to limit the sub pixel edge accuracy detection. From a full perspective internal camera model, we recover the true lens line of sight, around which the entire camera model revolves. It removes an image perspective bias that created a systematic scale, range, pose and shape bias in telemetry. Chromatic distortion's interference with Bayer pattern interpolation is the result of the basic assumption that edges in RGB are matching while they are not. The mixing of colors in the edge sensing of Bayer interpolation creates a sub pixel edge bias. Other shear bias sources also interfere with the true recovery of the lens line of sight.-shear and scale bias added by homography-lens model decentering terms added shear All those errors sources are systematic, and cannot be averaged out by taking multiple samples.

The stereo matching algorithms for binocular vision are very popular and widely used. Still, the algorithms may have lower matching quality or higher time complexity. Matching can be viewed as a process of finding the degree of correlation between two groups of data. This area belongs to the one of the most explored topics in stereo vision. The depth value can be found by the disparity estimat ion by taking advantage of the similarity in these two views, which can be captured at the same time in a depth generation algorithm. It is not easy to find the accurate depth value if there is high similarity in color sp aces around the area. Stereo matchi ng is a fundamental problem in computer vision that estimates depth of a 3D scene with a pair of images. This paper presents the fundamental steps for finding depth extraction and related terms

The depth of field (DoF) effect is a useful tool in photography and cinematography because of its aesthetic value. However, capturing and displaying dynamic DoF effect were until recently a quality unique to expensive and bulky movie cameras. A computational approach to generate realistic DoF effects for mobile devices such as tablets is proposed. We first calibrate the rear-facing stereo cameras and rectify the stereo image pairs through FCam API, then generate a low-res disparity map using graph cuts stereo matching and subsequently upsample it via joint bilateral upsampling. Next, we generate a synthetic light field by warping the raw color image to nearby viewpoints, according to the corresponding values in the upsampled high-resolution disparity map. Finally, we render dynamic DoF effect on the tablet screen with light field rendering. The user can easily capture and generate desired DoF effects with arbitrary aperture sizes or focal depths using the tablet only, with no additional hardware or software required. The system has been examined in a variety of environments with satisfactory results, according to the subjective evaluation tests. 1 Introduction Dynamic depth of field (DoF) effect is a useful tool in photography and cinematography because of its aesthetic value. Capturing and displaying dynamic DoF effect were until recently a quality unique to expensive and bulky movie cameras. Problems such as radial distortion may also arise if the lens system is not setup properly. Recent advances in computational photography enable the user to refocus an image at any desired depth after it has been taken. The hand-held plenoptic camera 1 places a micro-lens array behind the main lens, so that each microlens image captures the scene from a slightly different viewpoint. By fusing these images together, one can generate photographs focusing at different depths. However, due to the spatial-angular tradeoff 2 of the light field camera, the resolution of the final rendered image is greatly reduced. To overcome this problem, Georgiev and Lumsdaine 3 introduced the focused plenoptic camera and significantly increased spatial resolution near the main lens focal plane. However, angular resolution is reduced and may introduce aliasing effects to the rendered image. Despite recent advances in computational light field imaging , the costs of plenoptic cameras are still high due to the complicated lens structures. Also, this complicated structure makes it difficult and expensive to integrate light field cameras into small hand-held devices like smartphones or tablets. Moreover, the huge amount of data generated by the plenop-tic camera prohibits it from performing light field rendering on video streams. To address this problem, we develop a light field rendering algorithm on mobile platforms. Because our algorithm works on regular stereo camera systems, it can be directly

Visual impairment and blindness caused by infectious diseases has been greatly reduced, but increasing numbers of people are at risk of age-related visual impairment. Visual information is the basis for most navigational tasks, so visually impaired individuals are at disadvantage because appropriate information about the surrounding environment is not available. With the recent advances in inclusive technology it is possible to extend the support given to people with visual impairment during their mobility. In this context we propose a system, named SmartVision, whose global objective is to give blind users the ability to move around in unfamiliar environments, whether indoor or outdoor, through a user friendly interface. This paper is focused mainly in the development of the computer vision module of the SmartVision system.

Following some comments on the nature of stereo perception as it relates to stereo video displays, a number of areas of interest are briefly reviewed and accompanied by extensive citations from the patent and technical literature. These include various methods of autostereoscopic display, stereoendoscopy, stereo sculpture, and holographic television. STEREOVISION AND ELECTRONIC DISPLAYS

The Depth of Field (DoF) effect is a useful tool in photography and cinematography because of its aesthetic values. However, capturing and displaying dynamic DoF effect was until recently a quality unique to expensive and bulky movie cameras. In this paper, we propose a computational approach to generate realistic DoF effects for mobile devices such as tablets. We first calibrate the rear-facing stereo cameras and rectify stereo image pairs through FCam API, then generate a low-res disparity map using graph cuts stereo matching and subsequently upsample it via joint bilateral upsampling. Next we generate a synthetic light field by warping the raw color image to nearby viewpoints according to corresponding values in the upsampled high resolution disparity map. Finally, we render dynamic DoF effect on the tablet screen with light field rendering. The user can easily capture and generate desired DoF effects with arbitrary aperture sizes or focal depths using the tablet only with no additional hardware or software required. The system has been tested in a variety of environments with satisfactory results.

Our work stems from the need to stretch the information that can be recovered from a highly pixelized image. Several sub pixel bias sources add up and degrade the overall accuracy in digital imaging, the biggest one being a systematic bias in the camera model itself. Our solution is a fully software image correction technique from a sub pixel calibrated camera. In the process, we uncovered several systematic biases in:

International Journal of Computer Vision and machine learning (IJCVML) is an open access, peer-reviewed journal that publishes articles which contribute new results in all areas of the advanced vision computing. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding advances in vision computing and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of vision computing.

Our camera model gives a single image scale, relating width, to height, to depth proportions in the image like no other model can. It exactly relates the camera image to its true 3D perspective representation, allowing the exact solution to plane target tracking in the single camera case. The target surface becomes a true metric of its distance to the 1:1 true scale image plane. We'll show you how we increased telemetry accuracy by 10:1 while cutting down computational time, how to avoid chromatic distortion, the extension to the classic stereo pair, and how to switch from single to stereo camera to cope with occlusion.

Due to their cost, high-end commercial 3D-DIC (digital image correlation) systems are still inaccessible for many laboratories or small factories interested in lab testing materials. These professional systems can provide reliable and rapid full-field measurements that are essential in some laboratory tests with high-strain rate events or high dynamic loading. However, in many stress-controlled experiments, such as the Brazilian tensile strength (BTS) test of compacted soils, samples are usually large and fail within a timeframe of several minutes. In those cases, alternative low-cost methods could be successfully used instead of commercial systems. This paper proposes a methodology to apply 2D-DIC techniques using consumer-grade cameras and the open-source image processing software DICe (Sandia National Lab) for monitoring the standardized BTS test. Unlike most previous studies that theoretically estimate systematic errors or use local measures from strain gauges for accuracy assessment, we propose a contrast methodology with independent full-field measures. The displacement fields obtained with the low-cost system are benchmarked with the professional stereo-DIC system Aramis-3D (GOM GmbH) in four BTS experiments using compacted soil specimens. Both approaches proved to be valid tools for obtaining full-field measurements and showing the sequence of crack initiation, propagation and termination in the BTS, constituting reliable alternatives to traditional strain gauges. Mean deviations obtained between the low-cost 2D-DIC approach and Aramis-3D in measuring in-plane components were 0.08 mm in the perpendicular direction of loading (ΔX) and 0.06 mm in the loading direction (ΔY). The proposed low-cost approach implies considerable savings compared to commercial systems.

In 2012, three new optical flow reference datasets have been published, two of them containing ground truth [1–3]. None of them contains ground truth for real-world, large-scale outdoor scenes with dynamically and independently moving objects. The reason is that no measurement devices exists to record such data with sufficiently high accuracy. Yet, ground truth is needed to assess the safety of e.g. driver assistance systems. To close this gap, based on existing, accurate ground truth, we analyse the performance of uninformed human motion annota-tors. Feature annotation bias and non-rigid motions are a major concern, limiting our results to pixel-accuracy. Our approach is the only way to create ground truth for dynamic outdoor sequences and feasible when-ever pixel-accuracy is sufficient for performance analysis and piecewise rigid motions dominate the scene. Finally, we show that our approach is highly effective with respect to annotation cost per frame compared to our baseline method [4].

Psychophysical experiments have demonstrated that it is possible to simultaneously perceive binocular depth and rivalry in plaids . Here, we used fMRI at 3T to image activity in the visual cortex while human subjects perceived depth and rivalry from plaids. Six subjects performed either a rivalry or depth task. The spatial frequencies of the near-vertical and diagonal components were, respectively: 2.5, 6.4 cpd; 6.4, 2.5 cpd; or 6.4, 6.4 cpd. The network of activated cortical areas was very similar for the depth compared to the rivalry task. Nevertheless, regions of superior and inferior parietal cortices (including intraparietal sulcus) were activated more during the depth than the rivalry task, independent of spatial frequency, whereas a bias toward rivalry was seen in a lateral occipital region, superior temporal sulcus, and retrosplenial and ventral temporal cortices. Several retinotopic areas in the visual cortex showed a preference for the task with the higher (V1, V2, V3) or lower spatial frequency component (MT+), regardless of the depth or rivalry condition. Our results indicate that depth and rivalry are processed in a similar network of cortical areas and are perceived simultaneously by coexisting in different spatial channels. These results place constraints on binocular vision models.

The International Journal of Information Technology, Modeling and Computing (IJITMC) is an open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology, Modeling and Computing. With the advances of Information Technology, there is an active multi-disciplinary research in the areas of IT, CSE, Modeling and Simulation with numerous applications in various fields. The International Journal of Information Technology, Modeling and Computing (IJITMC) is an abstracted and indexed international journal of high quality devoted to the publication of original research papers from IT, Modeling, CSE and Control Engineering with some emphasis on all areas and subareas of computer science, IT, scientific modeling, simulation, visualization and control systems and their broad range of applications.

The goal of the Portuguese project "SmartVision: active vision for the blind" is to develop a small, portable and cheap yet intelligent and reliable system for assisting the blind and visually impaired while navigating autonomously, both in-and outdoor. In this article we present an overview of the prototype, design issues, and its different modules which integrate GPS and Wi-Fi localisation with a GIS, passive RFID tags, and computer vision. The prototype addresses global navigation for going to some destiny, by following known landmarks stored in the GIS in combination with path optimisation, and local navigation with path and obstacle detection just beyond the reach of the white cane. The system does not replace the white cane but complements it, in order to alert the user to looming hazards. In addition, computer vision is used to identify objects on shelves, for example in a pantry or refrigerator. The user-friendly interface consists of a four-button hand-held box, a vibration actuator in the handle of the white cane, and speech synthesis. In the near future, passive RFID tags will be complemented by active tags for marking navigation landmarks, and speech recognition may complement or substitute the vibration actuator.