A dense stereo correspondence algorithm for hardware implementation with enhanced disparity selection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5138 LNAI, Issue , 2008, Pages 365-370

  Nalpantidis, Lazaros ^a   Sirakoulis, Georgios Ch ^a   Gasteratos, Antonios ^a  

^a DEMOCRITUS UNIVERSITY OF THRACE   (Greece)

Author keywords

Cellular automata; Stereo correspondence; Stereoscopic vision

Indexed keywords

ARTIFICIAL INTELLIGENCE; CELLULAR AUTOMATA; STEREO VISION;

ABSOLUTE DIFFERENCE; DENSE DISPARITY MAPS; DENSE STEREO CORRESPONDENCES; GAUSSIAN DISTRIBUTED; HARDWARE IMPLEMENTATIONS; REAL-TIME APPLICATION; STEREO CORRESPONDENCES; STEREOSCOPIC VISION;

STEREO IMAGE PROCESSING;

EID: 55349105845     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-87881-0_34     Document Type: Conference Paper

References (7)

1. Marr, D., Poggio, T.A.: Cooperative Computation of Stereo Disparity. Science 194, 283-287 (1976)
2. Murray, D., Little, J.J.: Using Real-Time Stereo Vision for Mobile Robot Navigation. Autonomous Robots 8, 161-171 (2000)
3. Jain, R., Kasturi, R., Schunck, B.G.: Machine vision. McGraw-Hill, Inc., New York (1995)
4. Scharstein, D., Szeliski, R.: A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms. International Journal of Computer Vision 47, 7-42 (2002)
5. http://vision.middlebury.edu/stereo/
6. von Neumann, J.: Theory of Self-Reproducing Automata. University of Illinois Press, Urbana (1966)
7. Scharstein, D., Szeliski, R.: High-accuracy stereo depth maps using structured light. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 195-202 (2003)