CVFX Lecture 15: Stereo correspondence

ECSE-6969 Computer Vision for Visual Effects Rich Radke, Rensselaer Polytechnic Institute Lecture 15: Stereo correspondence (3/20/14) 0:00:01 Stereo correspondence 0:02:09 Disparity 0:04:43 Differences between stereo and optical flow 0:11:42 Basic stereo algorithms 0:12:04 Sum of absolute differences 0:14:27 Birchfield-Tomasi measure 0:16:31 Census transform 0:20:46 Dynamic programming for stereo 0:25:19 Non-monotonic correspondence 0:26:53 The Ohta-Kanade algorithm 0:29:31 Stereo algorithm benchmarking 0:36:21 Graph cuts for stereo 0:52:07 Belief propagation for stereo 0:56:02 Occlusions and discontinuities 0:59:53 Incorporating segmentation 1:06:50 Stereo rigs for filming Follows Section 5.5 of the textbook. http://cvfxbook.com Key references: D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision, 47(1):7--42, Apr. 2002. http://dx.doi.org/10.1023/A:1014573219977 Y. Ohta and T. Kanade. Stereo by intra- and inter-scanline search using dynamic programming. IEEE Transactions on Pattern Analysis and Machine Intelligence, 7(2):139--54, Mar. 1985. http://dx.doi.org/10.1109/TPAMI.1985.4767639 Y. Boykov, O. Veksler, and R. Zabih. Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(11):1222--39, Nov. 2001. http://dx.doi.org/10.1109/34.969114 J. Sun, N.-N. Zheng, and H.-Y. Shum. Stereo matching using belief propagation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(7):787--800, July 2003. http://dx.doi.org/10.1109/TPAMI.2003.1206509