Kernelized temporal cut for online temporal segmentation and recognition

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

Volumn 7574 LNCS, Issue PART 3, 2012, Pages 229-243

  Gong, Dian ^a   Medioni, Gérard ^a   Zhu, Sikai ^a   Zhao, Xuemei ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION SEGMENTATION; CHANGE POINT DETECTION; CYCLIC MOTIONS; DEPTH SENSORS; HIGH DIMENSIONALITY; HILBERT; HUMAN MOTIONS; MOTION CAPTURE DATA; NON-PARAMETRIC; ON-LINE ALGORITHMS; REAL TIME; REAL-TIME SEGMENTATION; SEQUENCE MATCHING ALGORITHMS; SEQUENTIAL DATA; SPACE EMBEDDING; STATE-OF-THE-ART METHODS; TEMPORAL SEGMENTATIONS;

ALGORITHMS; SENSORS;

COMPUTER VISION;

EID: 84867888093     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33712-3_17     Document Type: Conference Paper

References (30)

1. Barbic, J., Safonova, A., Pan, J.Y., Faloutsos, C., Hodgins, J.K., Pollard, N.S.: Segmenting motion capture data into distinct behaviors. In: Proc. Graphics Interface, pp. 185-194 (2004)
2. Lv, F., Nevatia, R.: Recognition and Segmentation of 3-D Human Action Using HMM and Multi-class AdaBoost. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006, Part IV. LNCS, vol. 3954, pp. 359-372. Springer, Heidelberg (2006)
3. Laptev, I., Marszalek, M., Schmid, C., Rozenfeld, B.: Learning realistic human actions from movies. In: Proc. CVPR (2008)
4. Weinland, D., Özuysal, M., Fua, P.: Making Action Recognition Robust to Occlusions and Viewpoint Changes. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part III. LNCS, vol. 6313, pp. 635-648. Springer, Heidelberg (2010)
5. Zhong, H., Shi, J., Visontai, M.: Detecting unusual activity in video. In: Proc. CVPR, pp. 816-8231 (2004)
6. Zhou, F., De la Torre, F., Hodgins, J.K.: Hierarchical aligned cluster analysis for temporal clustering of human motion. Under review at IEEE PAMI (2011)
7. Niebles, J.C., Chen, C.-W., Fei-Fei, L.: Modeling Temporal Structure of Decomposable Motion Segments for Activity Classification. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part II. LNCS, vol. 6312, pp. 392-405. Springer, Heidelberg (2010)
8. Chen, J., Gupta, A.: Parametric Statistical Change-point Analysis. Birkhäuser (2000)
9. Adams, R.P., MacKay, D.J.: Bayesian online changepoint detection. University of Cambridge Technical Report (2007)
10. De la Torre, F., Campoy, J., Ambadar, Z., Conn, J.F.: Temporal segmentation of facial behavior. In: Proc. ICCV (2007)
11. Hofmann, T., Scholkopf, B., Smola, A.: Kernel methods in machine learning. Annals of Statistics 36, 1171-1220 (2008)
12. Smola, A.J., Gretton, A., Song, L., Schölkopf, B.: A Hilbert Space Embedding for Distributions. In: Hutter, M., Servedio, R.A., Takimoto, E. (eds.) ALT 2007. LNCS (LNAI), vol. 4754, pp. 13-31. Springer, Heidelberg (2007)
13. Gretton, A., Fukumizu, K., Harchaoui, Z., Sriperumbudur, B.: A fast, consistent kernel twosample test. In: NIPS, vol. 19, pp. 673-681 (2009)
14. Gretton, A., Borgwardt, K., Rasch, M., Scholkopf, B., Smola, A.: A kernel method for the two-sample-problem. In: NIPS, vol. 19, pp. 513-520 (2007)
15. Zhou, F., De la Torre, F.: Canonical time warping for alignment of human behavior. In: NIPS, vol. 22, pp. 2286-2294 (2009)
16. Xuan, X., Murphy, K.: Modeling changing dependency structure in multivariate time series. In: Proc. ICML (2007)
17. Saatci, Y., Turner, R., Rasmussen, C.: Gaussian process change point models. In: Proc. ICML (2010)
18. Desobry, F., Davy, M., Doncarli, C.: An online kernel change detection algorithm. IEEE Trans. on Signal Processing 53, 2961-2974 (2005)
19. Harchaoui, Z.,Bach, F., Moulines, E.:Kernel change-point analysis. In:NIPS 21, pp. 609-616 (2009)
20. Ng, A.Y., Jordan, M.I., Weiss, Y.: On spectral clustering: Analysis and an algorithm. In: NIPS, vol. 14, pp. 849-856 (2002)
21. von Luxburg, U.: A tutorial on spectral clustering. Statistics and Computing 17, 395-416 (2007)
22. Fox, E., Sudderth, E., Jordan, M.,Willsky, A.: Nonparametric bayesian learning of switching linear dynamical systems. In: NIPS 21, pp. 457-464 (2009)
23. Zelnik-Manor, L., Irani, M.: Statistical analysis of dynamic actions. IEEE PAMI 28, 1530-1535 (2006)
24. Satkin, S., Hebert, M.: Modeling the Temporal Extent of Actions. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part I. LNCS, vol. 6311, pp. 536-548. Springer, Heidelberg (2010)
25. Gong, D.,Medioni, G.: Dynamic manifold warping for view invariant action recognition. In: Proc. ICCV, pp. 571-578 (2011)
26. Hoai, M., Lan, Z., De la Torre, F.: Joint segmentation and classification of human actions in video. In: Proc. CVPR (2011)
27. Faivishevsky, L., Goldberger, J.: A nonparametric information theoretic clustering algorithm. In: Proc. ICML, pp. 351-358 (2010)
28. Bach, F.R., Jordan, M.I.: Kernel independent component analysis. JMLR 3, 1-48 (2003)
29. Laptev, I., Belongie, S., Perez, P., Wills, J.: Periodic motion detection and segmentation via approximate sequence alignment. In: Proc. ICCV, pp. 816-8231 (2005)
30. Sigal, L., Balan, A.O., Black, M.J.: Humaneva: Synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion. IJCV 87, 4-27 (2010)