Stereo matching with mumford-shah regularization and occlusion handling

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 32, Issue 11, 2010, Pages 2071-2084

  Ben Ari, Rami ^a   Sochen, Nir ^b  

^a ORBOTECH LTD   (Israel)

^b TEL AVIV UNIVERSITY   (Israel)

Author keywords

Mumford Shah functional; occlusion handling; Stereo matching; Total Variation; variational stereo vision

Indexed keywords

MUMFORD-SHAH FUNCTIONALS; OCCLUSION HANDLING; STEREO MATCHING; TOTAL VARIATION; VARIATIONAL STEREO VISION;

STEREO VISION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; METHODOLOGY; PHOTOGRAPHY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; PATTERN RECOGNITION, AUTOMATED; PHOTOGRAMMETRY;

EID: 78149282989     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2010.32     Document Type: Article

References (50)

1. R. Alicandro, A. Braides, and J. Shah, "Free-Discontinuity Problems via Functionals Involving P-Norm of the Gradient and Their Approximation," Interface and Free Boundaries, vol. 1, pp. 17-37, 1999.
2. L. Alvarez, R. Deriche, J. Sanchez, and J. Weickert, "Dense Disparity Map Estimation Respecting Image Discontinuities: A PDE and Scale-Space Based Approach," J. Visual Comm. and Image Representation, vol. 13, pp. 3-21, 2002.
3. L. Ambrosio and V.M. Tortorelli, "Approximation of Functionals Depending on Jumps by Elliptic Functionals via T-Convergence," Comm. Pure and Applied Math., vol. 43, pp. 999-1036, 1990.
4. T. Amiaz and N. Kiryati, "Dense Discontinuous Optical Flow via Contour Based Segmentation," Proc. IEEE Int'l Conf. Image Processing, vol. 3, pp. 1264-1267, 2005.
5. Anonymous Stereo Matching Based on Under and Over-Segmentation with Occlusion Handling http://vision.middle bury.edu/stereo/eval/ 2010.
6. L. Bar, A. Brook, N. Sochen, and N. Kiryati, "Deblurring of Color Images Corrupted by Impulsive Noise," IEEE Trans. Image Processing, vol. 16, no. 4, pp. 1101-1111, Apr. 2007.
7. R. Ben-Ari and N. Sochen, "Variational Stereo Vision with Sharp Discontinuities and Occlusion Handling," Proc. IEEE Int'l Conf. Computer Vision, pp. 1-7, 2007.
8. M. Bleyer and M. Gelautz, "A Layered Stereo Algorithm Using Image Segmentation and Global Visibility Constraints," Proc. IEEE Int'l Conf. Image Processing, vol. 5, pp. 2997-3000, 2004.
9. M.Z. Brown, D. Burschka, and G.D. Hager, "Advances in Computational Stereo," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 8, pp. 993-1008, Aug. 2003.
10. T. Brox, A. Bruhn, N. Papenberg, and J. Weickert, "High Accuracy Optical Flow Estimation Based on a Theory for Warping," Proc. Eighth European Conf. Computer Vision, pp. 25-36, 2004.
11. T. Chan and L. Vese, "Active Contours without Edges," IEEE Trans. Image Processing, vol. 10, no. 2, pp. 266-277, Feb. 2001.
12. G. Dal Maso, "An Introduction to T-Convergence," Progress in Nonlinear Differential Equations and Their Applications, Birkhauser, 1993.
13. U.R. Dhond and J.K. Aggarwal, "Stereo Matching in Presence of Narrow Occluding Objects Using Dynamic Disparity Search," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 7, pp. 719-724, July 1995.
14. L.C. Evans and R.F. Gariepy, Measure Theory and Fine Properties of Functions. CRC Press, 1992.
15. L. Di Stefano, F. Tombari, S. Mattoccia, "Segmentation-Based Adaptive Support for Accurate Stereo Correspondence," Proc. IEEE Pacific-Rim Symp. Image and Video Technology, 2007.
16. A. Fusiello, V. Roberto, and E. Trucco, "Efficient Stereo with Multiple Windowing," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 858-863, 1997.
17. S. Gehrig and U. Franke, "Improving Sub-Pixel Accuracy for Long Range Stereo," Proc. IEEE Int'l Conf. Computer Vision VRML Workshop, 2007.
18. D. Geiger, B. Landendorf, and A.L. Yuille, "Occlusions and Binocular Stereo," Int'l J. Computer Vision, vol. 14, no. 3, pp. 211-226, 1995.
19. H. Hirschmüller, "Stereo Processing by Semi-Global Matching and Mutual Information," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 2, pp. 328-341, Feb. 2008.
20. T. Kanade and M. Okutomi, "A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiments," IEEE Trans. Pattern Recognition and Machine Intelligence, vol. 16, no. 9, pp. 920-932, Sept. 1994.
21. H. Kim and K. Sohn, "Hierarchical Disparity Estimation with Energy Based Regularization," Proc. 10th IEEE Int'l Conf. Image Processing, vol. 1, pp. 373-376, 2003.
22. A. Klaus, M. Sormann, and K. Karner, "Segment-Based Stereo Matching Using Belief Propagation and Self-Adapting Dissimilarity Measure," Proc. Int'l Conf. Pattern Recognition, vol. 3, pp. 15-18, 2006.
23. M. Klodt, T. Schoenemann, K. Kolev, M. Schikora, and D. Cremers, "An Experimental Comparison of Discrete and Continuous Shape Optimization Methods," Proc. European Conf. Computer Vision, 2008.
24. K. Kolmogorov and R. Zabih, "Computing Visual Correspondence with Occlusions Using Graph Cuts," Proc. IEEE Int'l Conf. Computer Vision, vol. 2, pp. 508-515, 2001.
25. 1 Minimization," Proc. 36th IEEE Conf. Decision and Control, vol. 2, pp. 1125-1129, 1997.
26. C. Lei, J. Selzer, and Y.H. Yang, "Region Tree Based Stereo Using Dynamic Programming Optimization," Proc. IEEE Proc. Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 2378-2385, 2006.
27. A.R. Mansouri, A. Mitiche, and J. Konard, "Selective Image Diffusion: Application to Disparity Estimation," Proc. IEEE Int'l Conf. Image Processing, vol. 3, pp. 114-118, 1998.
28. D. Marr and T.A. Poggio, "Cooperative Computation of Stereo Disparity," Science, vol. 194, no. 4262, pp. 283-287, 1976.
29. S. Mattoccia, S. Giardino, and A. Gambini, "Accurate and Efficient Cost Aggregation Strategy for Stereo Correspondence Based on Approximated Joint Bilateral Filtering," Proc. Asian Conf. Computer Vision, 2009.
30. W. Miled and J.C. Pesquet, "Disparity Map Estimation Using a Total Variation Bound," Proc. Third Canadian Conf. Computer and Robot Vision.
31. D. Mumford and J. Shah, "Optimal Approximations by Piecewise Smooth Functions and Associated Variational Problems," Comm. Pure and Applied Math., vol. 42, pp. 577-684, 1989.
32. S. Osher and J.A. Sethian, "Fronts Propagating with Curvature-Dependent Speed: Algorithms Based on Hamilton-Jacobi Formulations," J. Computational Physics, vol. 79, pp. 577-684, 1988.
33. Middlebury Optical Flow Benchmark Page. http://vision. middlebury.edu/flow/ 2010.
34. Middlebury Stereo Benchmark Page. http://vision.middlebury. edu/stereo/ 2010.
35. T. Pock, T. Schoenemann, G. Graber, H. Bischof, and D. Cremers, "A Convex Formulation of Continuous Multi-Label Problems," Proc. European Conf. Computer Vision, 2008.
36. L. Robert and R. Deriche, "Dense Depth Map Reconstruction: A Minimization and Regularization Approach Which Preserves Discontinuities," Proc. European Conf. Computer Vision, pp. 439-451, 1996.
37. D. Scharstein and R. Szeliski, "A Taxonomy and Evaluation of Dense Two Frame Stereo Correspondence Algorithms," Int'l J. Computer Vision, vol. 47, no. 1, pp. 7-42, 2002.
38. C. Schmid and A. Zisserman, "The Geometry and Matching of Curves in Multiple Views," Proc. European Conf. Computer Vision, pp. 104-118, 1998.
39. J. Shah, "Segmentation By Nonlinear Diffusion," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 202-207, 1991.
40. J. Shah, "A Nonlinear Diffusion Model for Discontinuous Disparity and Half-Occlusions in Stereo," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 34-40, 1993.
41. N. Slesareva, A. Bruhn, and J. Weickert, "Optical Flow Goes Stereo: A Variational Method for Estimating Discontinuity-Preserving Dense Disparity Maps," Proc. 27th DAGM Symp. Pattern Recognition, W. Kropatsch, R. Sablatnig, and A. Hanbury, eds., pp. 33-40, 2005.
42. J. Sun, Y. Li, S.B. Kang, and H.-Y. Shum, "Symmetric Stereo Matching for Occlusion Handling," Proc. IEEE Int'l Conf. Computer Vision and Pattern Recognition, pp. 399-406, 2005.
43. R. Kimmel, T. Nir, and A.M. Bruckstein, "Over-Parametrized Variational Optical Flow," Int'l J. Computer Vision, vol. 76, no. 2, pp. 205-216, 2008.
44. A.N. Tikhonov and V.Y. Arsenin, Solutions of Ill-Posed Problems. Winston and Sons, 1977.
45. V. Venkateswar and R. Chellapa, "Hierarchical Stereo and Motion Correspondence Using Feature Grouping," Int'l J. Computer Vision, vol. 15, pp. 245-269, 1995.
46. L.A. Vese and T.F. Chan, "A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model," Int'l J. Computer Vision, vol. 50, no. 3, pp. 271-293, 2002.
47. J. Weickert, Anisotropic Diffusion in Image Processing. Teubner Stuttgart, 1998.
48. Q. Yáng, R.Y.L. Wang, H. Stewénius, and D. Nistér, "Stereo Matching with Color-Weighted Correlation, Hierarchial Belief Propagation and Occlusion Handling," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 2347-2354, 2006.
49. Q. Yáng, R. Yang, J. Davis, and D. Nistér, "Spatial-Depth Super Resolution for Range Images," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2007.
50. K. Yoon and I. Kweon, "Locally Adaptive Support-Weight Approach for Visual Correspondence Search," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 924-931, 2005.