Towards longer long-range motion trajectories

BMVC 2012 - Electronic Proceedings of the British Machine Vision Conference 2012

Volumn , Issue , 2012, Pages

  Rubinstein, Michael ^a   Liu, Ce ^b   Freeman, William T ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b MICROSOFT RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER VISION; MOTION ESTIMATION;

ACTION RECOGNITION; COMBINATORIAL ASSIGNMENT; INITIAL ESTIMATE; MOTION REPRESENTATION; MOTION TRACKING METHODS; MOTION TRAJECTORIES; SHORT TRAJECTORIES; SPATIO-TEMPORAL REGULARIZATIONS;

TRAJECTORIES;

EID: 84898432561     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/C.26.53     Document Type: Conference Paper

References (22)

1. S. Baker, D. Scharstein, JP Lewis, S. Roth, M.J. Black, and R. Szeliski. A database and evaluation methodology for optical flow. In Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on, pages 1-8. IEEE, 2007.
2. J. Berclaz, F. Fleuret, and P. Fua. Multiple object tracking using flow linear programming. In Performance Evaluation of Tracking and Surveillance (PETS-Winter), 2009 Twelfth IEEE International Workshop on, pages 1-8. IEEE, 2009.
3. T. Brox and J. Malik. Large displacement optical flow: descriptor matching in variational motion estimation. IEEE transactions on pattern analysis and machine intelligence, 33(3):500-513, 2011.
4. T.S. Cho, S. Avidan, and W.T. Freeman. The patch transform. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 32(8):1489-1501, 2010.
5. F. Fleuret, J. Berclaz, R. Lengagne, and P. Fua. Multicamera people tracking with a probabilistic occupancy map. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 30(2):267- 282, 2008.
6. W. Ge and R.T. Collins. Multi-target data association by tracklets with unsupervised parameter estimation. In BMVC, volume 96, 2008.
7. B. K. P. Horn and B. G. Schunck. Determing optical flow. Artificial Intelligence, 17:185-203, 1981.
8. H. Jiang, S. Fels, and J.J. Little. A linear programming approach for multiple object tracking. In Computer Vision and Pattern Recognition, 2007. CVPR'07. IEEE Conference on, pages 1-8. IEEE, 2007.
9. Biliana Kaneva, Antonio Torralba, and William T. Freeman. Evaluating image feaures using a photorealistic virtual world. In IEEE International Conference on Computer Vision, pages 2282- 2289, 2011.
10. B. Leibe, K. Schindler, N. Cornelis, and L. Van Gool. Coupled object detection and tracking from static cameras and moving vehicles. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 30(10):1683-1698, 2008.
11. Y. Li, C. Huang, and R. Nevatia. Learning to associate: Hybridboosted multi-target tracker for crowded scene. In Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on, pages 2953-2960. IEEE, 2009.
12. C. Liu, W.T. Freeman, E.H. Adelson, and Y. Weiss. Human-assisted motion annotation. In Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, pages 1-8. IEEE, 2008.
13. B. Lucas and T. Kanade. An iterative image registration technique with an application to stereo vision. In Proceedings of the International Joint Conference on Artificial Intelligence, pages 674-679, 1981.
14. P. Nillius, J. Sullivan, and S. Carlsson. Multi-target tracking-linking identities using bayesian network inference. In Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, volume 2, pages 2187-2194. IEEE, 2006.
15. A. Rav-Acha, P. Kohli, C. Rother, and A. Fitzgibbon. Unwrap mosaics: A new representation for video editing. In ACM SIGGRAPH 2008 papers, pages 1-11. ACM, 2008.
16. P. Sand and S. Teller. Particle video: Long-range motion estimation using point trajectories. In Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, volume 2, pages 2195-2202. IEEE, 2006.
17. C. Schuldt, I. Laptev, and B. Caputo. Recognizing human actions: A local svm approach. In Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on, volume 3, pages 32-36. IEEE, 2004.
18. J. Shi and C. Tomasi. Good features to track. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR'94), pages 593-600, Seattle, June 1994.
19. B. Song, T.Y. Jeng, E. Staudt, and A. Roy-Chowdhury. A stochastic graph evolution framework for robust multi-target tracking. European Conference on Computer Vision (ECCV).
20. Ju Sun, Yadong Mu, Shuicheng Yan, and Loong Fah Cheong. Activity recognition using dense long-duration trajectories. In ICME, pages 322-327, 2010.
21. N. Sundaram, T. Brox, and K. Keutzer. Dense point trajectories by gpu-accelerated large displacement optical flow. Computer Vision-ECCV 2010, pages 438-451, 2010.
22. H. Wang, A. Klaser, C. Schmid, and C.L. Liu. Action recognition by dense trajectories. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 3169-3176. IEEE, 2011.