Stereo vision depth estimation methods for robotic applications

Vision is undoubtedly the most important sense for humans. Apart from many other low and higher level perception tasks, stereo vision has been proven to provide remarkable results when it comes to ...

[1]  Jurgen Vandorpe,et al.  Exact dynamic map building for a mobile robot using geometrical primitives produced by a 2D range finder , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[2]  In-So Kweon,et al.  Correspondence Search in the Presence of Specular Highlights Using Specular-Free Two-Band Images , 2006, ACCV.

[3]  Takeo Kanade,et al.  A Cooperative Algorithm for Stereo Matching and Occlusion Detection , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Rihard Karba,et al.  Wide-angle camera distortions and non-uniform illumination in mobile robot tracking , 2004, Robotics Auton. Syst..

[5]  Antonios Gasteratos,et al.  Review of Stereo Vision Algorithms: From Software to Hardware , 2008 .

[6]  Masanori Hariyama,et al.  Reliable stereo matching for highly-safe intelligent vehicles and its VLSI implementation , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[7]  Yiannis Aloimonos,et al.  Robust Contrast Invariant Stereo Correspondence , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[8]  Mark A. Horowitz,et al.  Light field video camera , 2000, IS&T/SPIE Electronic Imaging.

[9]  N. Hautiere,et al.  Road Segmentation Supervised by an Extended V-Disparity Algorithm for Autonomous Navigation , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[10]  Don Ray Murray,et al.  Using Real-Time Stereo Vision for Mobile Robot Navigation , 2000, Auton. Robots.

[11]  William B. Thompson,et al.  Disparity Analysis of Images , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Georgios Ch. Sirakoulis,et al.  IARP/EURON Workshop on Robotics for Risky Interventions and Environmental Surveillance , 2009 .

[13]  Hans P. Moravec.  Certainty grids for mobile robots , 1987 .

[14]  Antonios Gasteratos,et al.  Biologically and psychophysically inspired adaptive support weights algorithm for stereo correspondence , 2010, Robotics Auton. Syst..

[15]  Tom Ziemke,et al.  Epigenetic robotics : modelling cognitive development in robotic systems Action editor : , 2004 .

[16]  Rafael Mayoral,et al.  Evaluation of correspondence errors for stereo , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[17]  Cheng Lei,et al.  Region-Tree Based Stereo Using Dynamic Programming Optimization , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[18]  David A. Green,et al.  A Comparison of Real-Time Obstacle Avoidance Methods for Mobile Robots , 1991, ISER.

[19]  Ruigang Yang,et al.  Real-time consensus-based scene reconstruction using commodity graphics hardware , 2002, 10th Pacific Conference on Computer Graphics and Applications, 2002. Proceedings..

[20]  Horst Bischof,et al.  Hierarchical Disparity Estimation with Programmable 3D Hardware , 2004 .

[21]  In-So Kweon,et al.  Stereo Matching with Symmetric Cost Functions , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[22]  Tetsuya Yagi,et al.  Binocular robot vision emulating disparity computation in the primary visual cortex , 2008, Neural Networks.

[23]  Bharti,et al.  Classification of Alzheimer's from T2 Trans-Axial Brain MR Images: A Comparative Study of Feature Extraction Techniques , 2012, Int. J. Comput. Vis. Image Process..

[24]  Antonios Gasteratos,et al.  Stereovision-Based Algorithm for Obstacle Avoidance , 2009, ICIRA.

[25]  Leonard McMillan,et al.  A Real-Time Distributed Light Field Camera , 2002, Rendering Techniques.

[26]  Yoram Koren,et al.  Real-time obstacle avoidance for fact mobile robots , 1989, IEEE Trans. Syst. Man Cybern..

[27]  Yoram Koren,et al.  Real-time obstacle avoidance for fast mobile robots in cluttered environments , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[28]  Antonios Gasteratos,et al.  Obtaining Reliable Depth Maps for Robotic Applications from a Quad-Camera System , 2009, ICIRA.

[29]  Roger J. Green,et al.  Applied Signal and Image Processing: Multidisciplinary Advancements , 2011 .

[30]  Uwe M. Nassal.  Motion coordination and reactive control of autonomous multi‐manipulator systems , 1996 .

[31]  Oliver Schreer.  Stereo Vision-Based Navigation in Unknown Indoor Environment , 1998, ECCV.

[32]  Qican Zhang,et al.  Local stereo matching with adaptive support-weight, rank transform and disparity calibration , 2008, Pattern Recognit. Lett..

[33]  Abbas Mohammed.  Application of Novel Signal Processing Algorithms for the Detection and Minimization of Skywave Interfering Signals in Loran Receivers , 2011 .

[34]  Andrew Hogue,et al.  Underwater environment reconstruction using stereo and inertial data , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

[35]  James J. Little,et al.  Autonomous vision-based robotic exploration and mapping using hybrid maps and particle filters , 2009, Image Vis. Comput..

[36]  Hong Jeong,et al.  Generalized Trellis Stereo Matching with Systolic Array , 2004, ISPA.

[37]  Carver A. Mead,et al.  Neuromorphic electronic systems , 1990, Proc. IEEE.

[38]  Yoram Koren,et al.  The vector field histogram-fast obstacle avoidance for mobile robots , 1991, IEEE Trans. Robotics Autom..

[39]  Reinhard Männer,et al.  Calculating Dense Disparity Maps from Color Stereo Images, an Efficient Implementation , 2004, International Journal of Computer Vision.

[40]  Yiannis Aloimonos,et al.  A Roadmap to the Integration of Early Visual Modules , 2007, International Journal of Computer Vision.

[41]  Heiko Hirschmüller,et al.  Evaluation of Cost Functions for Stereo Matching , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[42]  Giuseppe Marino,et al.  Neural adaptive stereo matching , 2004, Pattern Recognit. Lett..

[43]  W. James MacLean,et al.  A Real-Time Large Disparity Range Stereo-System Using FPGAs , 2006, ACCV.

[44]  Robert C. Bolles,et al.  Localization and Mapping for Autonomous Navigation in Outdoor Terrains : A Stereo Vision Approach , 2007, 2007 IEEE Workshop on Applications of Computer Vision (WACV '07).

[45]  Jun Zhao,et al.  Global Correlation Based Ground Plane Estimation Using V-Disparity Image , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[46]  Antonios Gasteratos,et al.  Stereo vision for robotic applications in the presence of non-ideal lighting conditions , 2010, Image Vis. Comput..

[47]  Richard Szeliski,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, International Journal of Computer Vision.

[48]  Jia Yunde,et al.  Trinocular Cooperative Stereo Vision and Occlusion Detection , 2006, 2006 IEEE International Conference on Robotics and Biomimetics.

[49]  O. Brock,et al.  Robots in Human Environments: Basic Autonomous Capabilities , 1999, Int. J. Robotics Res..

[50]  Ajay Luthra,et al.  Overview of the H.264/AVC video coding standard , 2003, IEEE Trans. Circuits Syst. Video Technol..

[51]  Alonzo Kelly,et al.  Stereo Vision Enhancements for Low-Cost Outdoor Autonomous Vehicles , 1998 .

[52]  Jill M. Boyce,et al.  Fast mode decision and motion estimation for JVT/H.264 , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[53]  Hong Jeong,et al.  Real-time Stereo Vision FPGA Chip with Low Error Rate , 2007, 2007 International Conference on Multimedia and Ubiquitous Engineering (MUE'07).

[54]  Giorgio Metta,et al.  Epigenetic robotics: modelling cognitive development in robotic systems , 2005, Cognitive Systems Research.

[55]  Robert C. Bolles,et al.  Outdoor Mapping and Navigation Using Stereo Vision , 2006, ISER.

[56]  Jean-Charles Pinoli,et al.  Logarithmic Adaptive Neighborhood Image Processing (LANIP): Introduction, Connections to Human Brightness Perception, and Application Issues , 2007, EURASIP J. Adv. Signal Process..

[57]  Avinash C. Kak,et al.  Vision-based navigation by a mobile robot with obstacle avoidance using single-camera vision and ultrasonic sensing , 1998, IEEE Trans. Robotics Autom..

[58]  Luca Iocchi,et al.  A Multiresolution Stereo Vision System for Mobile Robots , 1998 .

[59]  In-So Kweon,et al.  Adaptive Support-Weight Approach for Correspondence Search , 2006, IEEE Trans. Pattern Anal. Mach. Intell..

[60]  Yiannis Aloimonos,et al.  Shape and the Stereo Correspondence Problem , 2005, International Journal of Computer Vision.

[61]  Peter I. Corke.  The Machine Vision Toolbox: a MATLAB toolbox for vision and vision-based control , 2005, IEEE Robotics & Automation Magazine.

[62]  Gérard G. Medioni,et al.  Stereo using monocular cues within the tensor voting framework , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[63]  Antonios Gasteratos,et al.  Efficient hierarchical matching algorithm for processing uncalibrated stereo vision images and its hardware architecture , 2011 .

[64]  Georgios Ch. Sirakoulis,et al.  A Dense Stereo Correspondence Algorithm for Hardware Implementation with Enhanced Disparity Selection , 2008, SETN.

[65]  Lakhmi C. Jain,et al.  Path Planning and Obstacle Avoidance for Autonomous Mobile Robots: A Review , 2006, KES.

[66]  Jean-Philippe Tarel,et al.  Real time obstacle detection in stereovision on non flat road geometry through "v-disparity" representation , 2002, Intelligent Vehicle Symposium, 2002. IEEE.