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Hardware Implementation of a Spline-Based Genetic Algorithm for Embedded Stereo Vision Sensor Providing Real-Time Visual Guidance to the Visually Impaired  [cached]
Dah-Jye Lee,Jonathan D. Anderson,James K. Archibald
EURASIP Journal on Advances in Signal Processing , 2008, DOI: 10.1155/2008/385827
Abstract: Many image and signal processing techniques have been applied to medical and health care applications in recent years. In this paper, we present a robust signal processing approach that can be used to solve the correspondence problem for an embedded stereo vision sensor to provide real-time visual guidance to the visually impaired. This approach is based on our new one-dimensional (1D) spline-based genetic algorithm to match signals. The algorithm processes image data lines as 1D signals to generate a dense disparity map, from which 3D information can be extracted. With recent advances in electronics technology, this 1D signal matching technique can be implemented and executed in parallel in hardware such as field-programmable gate arrays (FPGAs) to provide real-time feedback about the environment to the user. In order to complement (not replace) traditional aids for the visually impaired such as canes and Seeing Eyes dogs, vision systems that provide guidance to the visually impaired must be affordable, easy to use, compact, and free from attributes that are awkward or embarrassing to the user. ¢ € Seeing Eye Glasses, ¢ € an embedded stereo vision system utilizing our new algorithm, meets all these requirements.
A Specific Encoding Scheme for Genetic Stereo Correspondence Searching: Application to Obstacle Detection
Hazem Issa,Yassine Ruichek,Jack-Gérard Postaire
Journal of Systemics, Cybernetics and Informatics , 2003,
Abstract: Stereo correspondence is one of the most active research areas in computer vision. It consists in identifying features in two or more stereo images that are generated by the same physical feature in the three-dimensional space. In our approach, the matching problem is first turned into an optimization task where a fitness function, representing the constraints on the solution, is to be minimized. The optimization process is then performed by means of a genetic algorithm with a new encoding scheme. Experimental results are presented to demonstrate the robustness and the reliability of the proposed approach for obstacle detection in front of a vehicle using linear stereo vision.
Efficient Selection of Disambiguating Actions for Stereo Vision  [PDF]
Monika Schaeffer,Ron Parr
Computer Science , 2012,
Abstract: In many domains that involve the use of sensors, such as robotics or sensor networks, there are opportunities to use some form of active sensing to disambiguate data from noisy or unreliable sensors. These disambiguating actions typically take time and expend energy. One way to choose the next disambiguating action is to select the action with the greatest expected entropy reduction, or information gain. In this work, we consider active sensing in aid of stereo vision for robotics. Stereo vision is a powerful sensing technique for mobile robots, but it can fail in scenes that lack strong texture. In such cases, a structured light source, such as vertical laser line can be used for disambiguation. By treating the stereo matching problem as a specially structured HMM-like graphical model, we demonstrate that for a scan line with n columns and maximum stereo disparity d, the entropy minimizing aim point for the laser can be selected in O(nd) time - cost no greater than the stereo algorithm itself. In contrast, a typical HMM formulation would suggest at least O(nd^2) time for the entropy calculation alone.
Research on Stereo Matching Technology Based on Binocular Vision
Chang Su, Gongquan Tan, Yufeng Luo
Open Access Library Journal (OALib Journal) , 2019, DOI: 10.4236/oalib.1105755
With the rapid development of machine vision, binocular stereo vision based on the principle of parallax has gradually become the core of scientific re-search. This paper briefly presents the background and research significance, elaborates the research status of binocular vision robot at home and abroad and studies the checkerboard calibration method, and uses Matlab to complete binocular camera calibration. Stereo matching technology is the core and most difficult part of binocular stereoscopic 3D reconstruction research. Firstly, the image acquired after calibration is enhanced by gray scale transformation to make the image clearness optimal, and then use NCC (normalization cross-compilation). The algorithm performs the matching of left and right image pairs in the Matlab environment to generate an optimal matching disparity map.
Intelligent Indoor Mobile Robot Navigation Using Stereo Vision  [PDF]
Arjun B. Krishnan,Jayaram Kollipara
Computer Science , 2014,
Abstract: Majority of the existing robot navigation systems, which facilitate the use of laser range finders, sonar sensors or artificial landmarks, has the ability to locate itself in an unknown environment and then build a map of the corresponding environment. Stereo vision, while still being a rapidly developing technique in the field of autonomous mobile robots, are currently less preferable due to its high implementation cost. This paper aims at describing an experimental approach for the building of a stereo vision system that helps the robots to avoid obstacles and navigate through indoor environments and at the same time remaining very much cost effective. This paper discusses the fusion techniques of stereo vision and ultrasound sensors which helps in the successful navigation through different types of complex environments. The data from the sensor enables the robot to create the two dimensional topological map of unknown environments and stereo vision systems models the three dimension model of the same environment.
Hybrid Collaborative Stereo Vision System for Mobile Robots Formation
Flavio Roberti,Juan Marcos Toibero,Carlos Soria,Raquel Frizera Vassallo
International Journal of Advanced Robotic Systems , 2010,
Abstract: This paper presents the use of a hybrid collaborative stereo vision system (3D-distributed visual sensing using different kinds of vision cameras) for the autonomous navigation of a wheeled robot team. It is proposed a triangulation-based method for the 3D-posture computation of an unknown object by considering the collaborative hybrid stereo vision system, and this way to steer the robot team to a desired position relative to such object while maintaining a desired robot formation. Experimental results with real mobile robots are included to validate the proposed vision system.
Picture quiz: non-optical measures to support children with low vision
Community Eye Health Journal , 2012,
Abstract: Picture quiz on practical suggestions for supporting people with low vision.
Research on stereo vision pathplanning algorithms for mobile robots autonomous navigation
ZHANG Guowei,LU Qiuhong
重庆邮电大学学报(自然科学版) , 2009,
Abstract: Using stereo vision for autonomous mobile robot pathplanning is a hot technology. The environment mapping and pathplanning algorithms were introduced, and they were applied in the autonomous mobile robot experiment platform. Through experiments in the robot platform, the effectiveness of these algorithms was verified.
Extracting the Prevailed Patterns in Recognizing the Picture by the Human Vision
Ehsan Kamrani
International Journal of Advanced Robotic Systems , 2010,
Abstract: We have tried to present the most matched approaches with which the vision dose through numerous studying the segment fields and recognizing the picture. Here we define external pictures features as the prevailed picture features and then extract the locust point of minus decline and among these points. Of minus decline and among these points we have defined the points which match with the human vision specifications according to the defined factors in this research such as clarification sharpness roundness and adjacency and used them as copied systems. We have reviewed our proposed patterns for truth, correctness and validity through performing two empirical tests.
A Novel Solution for Camera Occlusion in Stereo Vision Technique  [PDF]
Junyi Lin,Kaiyong Jiang,Ming Chang
Advances in Mechanical Engineering , 2013, DOI: 10.1155/2013/253794
Abstract: Stereo version is a well-known technique for obtaining depth and surface information of objects from images captured by two cameras. In general, this technique is limited by camera occlusion inherent to grooved or steep profiles in 3D shape measurements. To alleviate this problem, a traditional dual-camera system accompanied with a projector based on the stereo vision principle is presented. The projector was considered as a virtual camera. Three sets of stereo vision systems were then obtained with each of the two cameras at the same global coordinates for 3D topography measurements. The data acquisition system constructed with the two real cameras was first calibrated. Then the two-camera-projector system can be calibrated based on the data obtained from the common measurement area of the three systems. Experiments were implemented to evaluate the accuracy of the merging profile integrated from the three sets of stereo vision systems. Experimental results show that the problem of camera occlusion encountered in the original dual-camera system was effectively resolved and a 0.05% error for the height measurement of a ladder-shaped specimen with camera occlusions was obtained in a measurement range of . 1. Introduction Accurate measurement of the 3D shape of objects is a rapidly expanding field, with applications in object recognition, inspection, design, and manufacturing [1]. Among the existing 3D shape measurement techniques, structured light [2] and stereo vision [3] are two of the most commonly used methods due to their advantages such as fast measurement, good accuracy, and noncontact nature. In both techniques, the most pressing concern that limits the measurable range is the camera occlusion introduced by the steep surface or shadow of the specimen. A solution to this problem combined a dual-camera system with structured illumination [4, 5]. This approach utilized two cameras to acquire images independently, so that the measured profile of one view can be extended by combining the measured range of the two cameras and removing the occlusion. However, since the two measured profiles were not based on the same coordinate system, the data integration process for the two different imaging systems is complicated and time consuming. In this study, a novel stereo vision system consisting of two cameras and a digital projector is presented. The structure is similar to the dual-camera structured light system but the measurement principle is different. In general, through comparison of information about a scene from two vantage points in a stereo version
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