Attribute regularization based human action recognition

IEEE Transactions on Information Forensics and Security

Volumn 8, Issue 10, 2013, Pages 1600-1609

  Zhang, Zhong ^a   Wang, Chunheng ^a   Xiao, Baihua ^a   Zhou, Wen ^a   Liu, Shuang ^a  

^a CASIA   (China)

Author keywords

Attribute regularization; human action; multitask learning

Indexed keywords

ATTRIBUTE REGULARIZATIONS; CLASSIFICATION ACCURACY; HIGH LEVEL SEMANTICS; HUMAN ACTIONS; HUMAN-ACTION RECOGNITION; MULTITASK LEARNING; SEMANTIC INFORMATION; SEMANTIC RELATIONSHIPS;

FLEXIBLE COUPLINGS; SEMANTICS;

GESTURE RECOGNITION;

EID: 84884513342     PISSN: 15566013     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIFS.2013.2258152     Document Type: Article

References (50)

1. J. K. Aggarwal and Q. Cai, "Human motion analysis: A review," in Proc. IEEE Workshop on Nonrigid and Articulated Motion, 1997, pp. 90-102.
2. A. Yilmaz and M. Shah, "Actions sketch: A novel action representation," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2005, pp. 984-989. (Pubitemid 43897299)
3. Z. Lin, Z. Jiang, and L. S. Davis, "Recognizing actions by shape-motion prototype trees," in Proc. IEEE Int. Conf. Comput. Vision, 2009, pp. 444-451.
4. F. Lv and R. Nevatia, "Single view human action recognition using key pose matching and viterbi path searching," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2007, pp. 1-8.
5. A. Efros, A. Berg, G. Mori, and J. Malik, "Recognizing action at a distance," in Proc. IEEE Int. Conf. Comput. Vision, 2003, pp. 726-733.
6. M. Raptis and S. Soatto, "Tracklet descriptors for action modeling and video analysis," in Proc. Eur.Conf.Comput. Vision, 2010, pp. 577-590.
7. J. Liu, Y. Yang, and M. Shah, "Learning semantic visual vocabularies using diffusion distance," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2009, pp. 461-468.
8. D. A. Vaquero, R. S. Feris, D. Tran, L. Brown, A. Hampapur, andM. Turk, "Attribute-based peopole search in surveillance environments," in Proc. IEEE Workshop Applicat. of Comput. Vision, 2009, pp. 1-8.
9. A. Kovashka, D. Parikh, and K. Grauman, "WhittleSearch: Image search with relative attribute feedback," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2012, pp. 2973-2980.
10. S. J. Pan and Q. Yang, "A survey on transfer learning," IEEE Trans. Knowl. Data Eng., vol. 22, no. 10, pp. 1345-1359, Oct. 2010.
11. S. I. Lee, V. Chatalbashev, D. Vickrey, and D. Koller, "Learning a meta-level prior for feature relevance from multiple related tasks," in Proc. Int. Conf. Machine Learning, 2007, pp. 489-496.
12. T. Jebara, "Multi-task feature and kernel selection for SVMs," in Proc. Int. Conf. Machine Learning, 2004, pp. 55-55.
13. P. Dollár, V. Rabaud, G. Cottrell, and S. Belongie, "Behavior recognition via sparse spatio-temporal features," in Proc. IEEE Int. Workshop Visual Surveillance and Performance Evaluat. of Tracking and Surveillance, 2005, pp. 65-72. (Pubitemid 46178025)
14. Z. Zhang, C.Wang, B. Xiao,W. Zhou, and S. Liu, "Action recognition using context-constrained linear coding," IEEE Signal Process. Lett., vol. 19, no. 7, pp. 439-442, Jul. 2012.
15. A. Farhadi, I. Endres, D. Hoiem, and D. Forsyth, "Describing objects by their attributes," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2009, pp. 1778-1785.
16. D. Parikh and K. Grauman, "Relative attributes," in Proc. IEEE Int. Conf. Comput. Vision, 2011, pp. 503-510, DOI: 10.1016/j.patcog. 2012.10.004.
17. N. Kumar, A. C. Berg, P. N. Belhumeur, and S. K. Nayar, "Attribute and simile classifiers for face verification," in Proc. IEEE Int. Conf. Comput. Vision, 2009, pp. 365-372.
18. Y.Wang and G.Mori, "A discriminative latent model of object classes and attributes," in Proc. Eur. Conf. on Comput. Vision, 2010, pp. 155-168.
19. S. J. Hwang, F. Sha, and K. Grauman, "Sharing features between objects and their attributes," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2011, pp. 1761-1768.
20. R. K. Ando and T. Zhang, "A framework for learning predictive structures from multiple tasks and unlabeled data," J. Mach. Learning Res., vol. 6, pp. 1817-1853, 2005.
21. A. Argyriou, T. Evgeniou, and M. Pontil, "Convex multi-task feature learning," Mach. Learning, vol. 73, no. 3, pp. 243-272, 2008.
22. J. Liu, S. Ji, and J. Ye, "Multi-task feature learning via efficient-norm minimization," in Proc. Twenty-Fifth Conf. Uncertainty in Artificial Intell., 2009, pp. 339-348.
23. G. Wang and D. Forsyth, "Joint learning of visual attributes, object classes and visual saliency," in Proc. IEEE Int. Conf. Comput. Vision, 2009, pp. 537-544.
24. I. Laptev, "On space-time interest points," Int. J. Comput. Vis., vol. 64, no. 2, pp. 107-123, 2005. (Pubitemid 41314645)
25. N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2005, pp. 886-893. (Pubitemid 43897286)
26. N. Dalal, B. Triggs, and C. Schmid, "Human detection using oriented histograms of flow and appearance," in Proc. Eur. Conf. Comput. Vision, 2006, pp. 428-441. (Pubitemid 44029745)
27. H. Wang, M. M. Ullah, A. Klaser, I. Laptev, and C. Schmid, "Evaluation of local spatio-temporal features for action recognition," in Proc. British Machine Vision Conf., London, U.K., 2009.
28. C. H. Lampert, H. Nickisch, and S. Harmeling, "Learning to detect unseen object classes by between-class attribute transfer," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2009, pp. 951-958.
29. C. C. Chang and C. J. Lin, "LIBSVM: A library for support vector machines," ACM Trans. Intelligent Syst. Tech., vol. 2, no. 3, pp. 27-27, 2001.
30. C. Schuldt, I. Laptev, and B. Caputo, "Recognizing human actions: A local SVM approach," in Proc. IEEE Int. Conf. Pattern Recognit., 2004, pp. 32-36.
31. D. Tran and A. Sorokin, "Human activity recognition with metric learning," in Proc. Eur. Conf. Comput. Vision, 2008, pp. 548-561.
32. J. Niebles, C. W. Chen, and F.-F. Li, "Modeling temporal structure of decomposable motion segments for activity classification," in Proc. Eur. Conf. Comput. Vision, 2010, pp. 392-405.
33. J. Liu, B. Kuipers, and S. Savarese, "Recognizing human actions by attributes," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2011, pp. 3337-3344.
34. J. Liu and M. Shah, "Learning human actions via information maximization," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2008, pp. 1-8.
35. M. S. Ryoo and J. K. Aggarwal, "Spatio-temporal relationship match: Video structure comparison for recognition of complex human activities," in Proc. IEEE Int. Conf. Comput. Vision, 2009, pp. 1593-1600.
36. A. Kovashka and K. Grauman, "Learning a hierarchy of discriminative space-time neighborhood features for human action recognition," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2010, pp. 2046-2053.
37. I. Laptev, M. Marszalek, C. Schmid, and B. Rozenfeld, "Learning realistic human actions from movies," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2008, pp. 1-8.
38. S. Savarese, A. DelPozo, J. C. Niebles, and F.-F. Li, "Spatial-Temporal correlatons for unsupervised action classification," in Proc. IEEE Workshop Motion and Video Comput., 2008, pp. 1-8.
39. J. Wang, Z. Chen, and Y. Wu, "Action recognition with multiscale spatio-temporal contexts," inProc. IEEE Int. Conf.Comput. Vision and Pattern Recognit., 2011, pp. 3185-3192.
40. Q.V.Le,W. Y. Zou, S. Y. Yeung, andA.Y.Ng, "Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2011, pp. 3361-3368.
41. M. Blank, L. Gorelick, E. Shechtman, M. Irani, and R. Basri, "Actions as space-time shapes," in Proc. IEEE Int. Conf. Comput. Vision, 2005, pp. 1395-1402. (Pubitemid 44042342)
42. A. Fathi and G. Mori, "Action recognition by learning mid-level motion features," in Proc. IEEE Int. Conf. Comput. Vision and Pattern Recognit., 2008, pp. 1-8.
43. L. Shao and R. Mattivi, "Feature detector and descriptor evaluation in human action recognition," in Proc. ACM Int. Conf. on Image and Video Retrieval, 2010, pp. 477-484.
44. T. Berg, A. Berg, and J. Shih, "Automatic attribute discovery and characterization from noisy web data," in Proc. Eur. Conf. Comput. Vision, 2010, pp. 663-676.
45. X. Zhen, L. Shao, D. Tao, and X. Li, "Embedding motion and structure features for human action recognition," IEEE Trans. Circuits Syst. Video Technol., DOI: 10.1109/TCSVT.2013.2240916 .
46. L. Liu, L. Shao, and P. Rockett, "Boosted key-frame selection and correlated pyramidal motion-feature representation for human action recognition," Pattern Recognit., vol. 46, no. 7, pp. 1810-1818, Jul. 2013.
47. L. Shao, L. Ji, Y. Liu, and J. Zhang, "Human action segmentation and recognition via motion and shape analysis," Pattern Recognit. Lett., vol. 33, no. 4, pp. 438-445, Mar. 2012.
48. L. Liu, L. Shao, and P. Rockett, "Genetic programming-evolved spatiotemporal descriptor for human action recognition," inProc. BritishMachine Vision Conf., Surrey, 2012.
49. S. Xiang, F. Nie, G. Meng, C. Pan, and C. Zhang, "Discriminative least squares regression for multiclass classification and feature selection0," IEEE Trans. Neural Netw. Learning Syst., vol. 23, no. 11, pp. 1738-1754, Nov. 2012.
50. S. Xiang, F. Nie, Y. Song, and C. Zhang, "Contour graph based human tracking and action sequence recognition," Pattern Recognit., vol. 41, no. 12, pp. 3653-3664, 2008.