Layered 4D representation and voting for grouping from motion

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 25, Issue 4, 2003, Pages 492-501

  Nicolescu, Mircea ^a   Medioni, Gérard ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; IMAGE ANALYSIS; IMAGE CODING; IMAGE ENHANCEMENT; PATTERN MATCHING; TENSORS;

MOTION ANALYSIS; PERCEPTUAL GROUPING; TENSOR VOTING;

COMPUTER VISION;

EID: 0038639323     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2003.1190574     Document Type: Article

References (34)

1. S. Ullman, The Interpretation of Visual Motion. MIT Press, 1979.
2. J. Barron, D. Fleet, and S. Beauchemin, "Performance of Optical Flow Techniques," Int'l J. Visual Computing, vol. 12, no. 1, pp. 43-77, 1994.
3. B. Horn and B. Schunck, "Determining Optical Flow," Artificial Intelligence, vol. 17, pp. 185-203, 1981.
4. B. Lucas and T. Kanade, "An Iterative Image Registration Technique with an Application to Stereo Vision," Proc. DARPA Image Understanding Workshop, pp. 121-130, 1981.
5. E. Simoncelli, E. Adelson, and D. Heeger, "Probability Distributions of Optical Flow," Proc. Conf. Computer Vision and Pattern Recognition, pp. 310-315, 1991.
6. H. Nagel and W. Enkelmann, "An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 8, pp. 565-593, 1986.
7. P. Anandan, "A Computational Framework and an Algorithm for the Measurement of Visual Motion," Int'l J. Visual Computing, vol. 2, pp. 283-310, 1989.
8. P. Burt and E. Adelson, "The Laplacian Pyramid as a Compact Image Code," IEEE Trans. Comm., vol. 31, pp. 532-540, 1983.
9. A. Singh, Optical Flow Computation: A Unified Perspective. IEEE CS Press, 1992.
10. D. Heeger, "Optical Flow using Spatiotemporal Filters," Int'l J. Visual Computing, vol. 1, pp. 279-302, 1988.
11. F. Heitz and P. Bouthemy, "Multimodal Estimation of Discontinuous Optical Flow Using Markov Random Fields," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 12, pp. 1217-1232, Dec. 1993.
12. M. Gelgon and P. Bouthemy, "A Region-Level Graph Labeling Approach to Motion-Based Segmentation," Proc. Conf. Computer Vision and Pattern Recognition, pp. 514-519, 1997.
13. C. Kervrann and F. Heitz, "A Markov Random Field Model-Based Approach to Unsupervised Texture Segmentation Using Local and Global Spatial Statistics," IEEE Trans. Image Processing, vol. 4, no. 6, pp. 856-862, 1995.
14. Y. Boykov, O. Veksler, and R. Zabih, "Markov Random Fields with Efficient Approximations," Proc. Conf. Computer Vision and Pattern Recognition, pp. 648-655, 1998.
15. S. Ghosal, "A Fast Scalable Algorithm for Discontinuous Optical Flow Estimation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 2, pp. 181-194, Feb. 1996.
16. R. Deriche, P. Kornprobst, and G. Aubert, "Optical Flow Estimation while Preserving its Discontinuities: A Variational Approach," Proc. Asian Conf. Computer Vision, pp. 290-295, 1995.
17. T. Darrell and A. Pentland, "Robust Estimation of a Multilayered Motion Representation," Proc. IEEE Workshop Visual Motion, pp. 173-178, 1991.
18. S. Ayer and H. Sawhney, "Layered Representation of Motion Video Using Robust Maximum Likelihood Estimation of Mixture Models and MDL Encoding," Proc. Int'l Conf. Computer Vision, pp. 777-784, 1995.
19. G. McLachlan and K. Basford, Mixture Models Inference and Applications to Clustering. Marcel Dekker, Inc., 1988.
20. S. Hsu, P. Anandan, and S. Peleg, "Accurate Computation of Optical Flow by Using Layered Motion Representations," Proc. Int'l Conf. Pattern Recognition, pp. 743-746, 1994.
21. A. Jepson and M. Black, "Mixture Models for Optical Flow Computation," Proc. Conf. Computer Vision and Pattern Recognition, pp. 760-761, 1993.
22. Y. Weiss, "Smoothness in Layers: Motion Segmentation Using Nonparametric Mixture Estimation," Proc. Conf. Computer Vision and Pattern Recognition, pp. 520-526, 1997.
23. M. Irani and S. Peleg, "Image Sequence Enhancement Using Multiple Motions Analysis," Proc. Conf. Computer Vision and Pattern Recognition, pp. 216-221, 1992.
24. J. Wang and E. Adelson, "Representing Moving Images with Layers," IEEE Trans. Image Processing Special Issue: Image Sequence Compression, vol. 3, no. 5, pp. 625-638, 1994.
25. D. Fleet, M. Black, and A. Jepson, "Motion Feature Detection Using Steerable Flow Fields," Proc. Conf. Computer Vision and Pattern Recognition, pp. 274-281, 1998.
26. J. Shi and J. Malik, "Motion Segmentation and Tracking Using Normalized Cuts," Proc. Int'l Conf. Computer Vision, pp. 1154-1160, 1998.
27. Y. Wu, T. Kanade, J. Cohn, and C. Li, "Optical Flow Estimation Using Wavelet Motion Model," Proc. Int'l Conf. Computer Vision, pp. 992-998, 1998.
28. J. Little, H. Bulthoff, and T. Poggio, "Parallel Optical Flow Using Local Voting," Proc. Int'l Conf. Computer Vision, pp. 454-459, 1988.
29. G. Medioni, M.-S. Lee, and C.-K. Tang, A Computational Framework for Segmentation and Grouping, Elsevier Science, 2000.
30. L. Gaucher and G. Medioni, "Accurate Motion Flow Estimation with Discontinuities," Proc. Int'l Conf. Computer Vision, pp. 695-702, 1999.
31. G. Guy and G. Medioni, "Inference of Surfaces, 3D Curves and Junctions from Sparse, Noisy 3D Data," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 11, pp. 1265-1277, Nov. 1997.
32. S. Arya, D. Mount, N. Netanyahu, R. Silvermann, and A. Wu, "An Optimal Algorithm for Approximate Nearest Neighbor Searching in Fixed Dimensions," J. ACM, vol. 45, no. 6, pp. 891-923, 1998.
33. J. Bergen, P. Burt, R. Hingorani, and S. Peleg, "A Three-Frame Algorithm for Estimating Two-Component Image Motion," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 9, pp. 886-896, Sept. 1992.
34. R. Szeliski, S. Avidan, and P. Anandan, "Layer Extraction from Multiple Images Containing Reflections and Transparency," Proc. Conf. Computer Vision and Pattern Recognition, pp. 246-253, 2000.