Supervised class-specific dictionary learning for sparse modeling in action recognition

Pattern Recognition

Volumn 45, Issue 11, 2012, Pages 3902-3911

  Wang, Haoran ^a,b   Yuan, Chunfeng ^b   Hu, Weiming ^b   Sun, Changyin ^a  

^a SOUTHEAST UNIVERSITY   (China)

^b INSTITUTE OF AUTOMATION   (China)

Author keywords

Action recognition; Compound feature; Motion segment; Sparse model; Supervised dictionary learning

Indexed keywords

ACTION RECOGNITION; COMPOUND FEATURES; CONSTRAINED TERMS; CONTINUOUS MOTIONS; DESCRIPTORS; DICTIONARY LEARNING; LOSS FUNCTIONS; LOW LEVEL; MOTION SEGMENTS; SPATIAL INFORMATIONS; SUPERVISED CLASSIFICATION; TEMPORAL ORDERING;

PATTERN RECOGNITION;

SOFTWARE ENGINEERING;

EID: 84862173236     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2012.04.024     Document Type: Article

References (53)

1. I. Laptev, M. Marszalek, C. Schmid, B. Rozenfeld, Learning realistic human actions from movies, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2008.
2. I. Laptev On space-time interest points International Journal of Computer Vision 64 2 2005 107 123 (Pubitemid 41314645)
3. J.C. Niebles, H. Wang, and L. Fei-Fei Unsupervised learning of human action categories using spatial-temporal words International Journal of Computer Vision 79 3 2008 299 318
4. A. Gilbert, J. Illingworth, R. Bowden, Fast realistic multi-action recognition using mined dense spatio-temporal features, in: Proceedings of the IEEE International Conference on Computer Vision, 2010.
5. H. Lee, A. Battle, R. Raina, and A.Y. Ng Efficient sparse coding algorithms Advances in Neural Information Processing Systems 2007
6. J. Yang, K. Yu, Y. Gong, T. Huang, Linear spatial pyramid matching using sparse coding for image classification, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2009.
7. Ignacio Ramirez, Pablo Sprechmann, Guillermo Sapiro, Classification and clustering via dictionary learning with structured incoherence and shared features, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2010.
8. L. Qiao, S. Chen, and X. Tan Sparsity preserving projections with applications to face recognition Pattern Recognition 43 1 2010 331 341
9. M. Fan, N. Gu, H. Qiao, and B. Zhang Sparse regularization for semi-supervised classification Pattern Recognition 44 8 2011 1777 1784
10. J. Mairal, F. Bach, J. Ponce, and G. Sapiro Supervised dictionary learning Advances in Neural Information Processing Systems 2008
11. D.M. Bradley, and J.A. Bagnell Differential sparse coding Advances in Neural Information Processing Systems 2008
12. Jinjun Wang, Jianchao Yang, Kai Yu, Fengjun Lv, Thomas Huang, Yihong Gong, Locality-constrained linear coding for image classification, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2010.
13. I. Kotsia, S. Zafeiriou, and I. Pitas Texture and shape information fusion for facial expression and facial action unit recognition Pattern Recognition 41 3 2008 833 851 (Pubitemid 47632661)
14. H. Jiang, M. Crew, Z. Li, Successive convex matching for action detection, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006.
15. T. Starner, A. Pentland, Visual recognition of American sign language using hidden Markov model, in: International Workshop on Automatic Face and Gesture Recognition, 1995.
16. J. Zhang, and S. Gong Action categorization with modified hidden conditional random field Pattern Recognition 43 1 2010 197 203
17. S. Xiang, F. Nie, Y. Song, and C. Zhang Contour graph based human tracking and action sequence recognition Pattern Recognition 41 12 2008 3653 3664
18. L. Gorelick, M. Blank, E. Shechtman, M. Irani, and R. Basri Actions as space-time shapes IEEE Transactions on Pattern Analysis and Machine Intelligence 29 12 2007 2247 2253 (Pubitemid 350124072)
19. A.F. Bobick, and J.W. Davis The recognition of human movement using temporal templates IEEE Transactions on Pattern Analysis and Machine Intelligence 23 3 2001 1257 1265
20. M. Ahmad, and S. Lee Human action recognition using shape and CLG-motion flow from multi-view image sequences Pattern Recognition 41 7 2008 2237 2252
21. S. Ali, and M. Shah Human action recognition in videos using kinematic features and multiple instance learning IEEE Transactions on Pattern Analysis and Machine Intelligence 32 2 2010 288 303
22. T. Mahmood, A. Vasilescu, S. Sethi, Recognition of action events from multiple video points, in: Proceedings of the IEEE International Conference on Computer Vision, 2001.
23. J. Liu, S. Ali, M. Shah, Recognizing human actions using multiple features, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2008.
24. P. Scovanner, S. Ali, M. Shah, A 3-dimensional SIFT descriptor and its application to action recognition, in: Proceedings of the International Conference on Multimedia, 2007.
25. M. Marszalek, I. Laptev, C. Schmid, Actions in context, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2009.
26. Y. Wang, and G. Mori Human action recognition by semilatent topic models IEEE Transactions on Pattern Analysis and Machine Intelligence 31 10 2009 1762 1774
27. S.F. Wong, T.K. Kim, R. Cipolla, Learning motion categories using both semantic and structural information, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2007.
28. B. Laxton, J. Lim, D. Kriegman, Leveraging temporal, contextual and ordering constraints for recognizing complex activities in video, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2007.
29. N. Ikizler, and D.A. Forsyth Searching for complex human activities with no visual examples International Journal of Computer Vision 80 3 2008 337 357
30. C. Sminchisescu, A. Kanaujia, and D. Metaxas Conditional models for contextual human motion recognition Computer Vision and Image Understanding 104 2 2006 1808 1815
31. A. Quattoni, S.B. Wang, L.P. Morency, M. Collins, and T. Darrell Hidden conditional random fields IEEE Transactions on Pattern Analysis and Machine Intelligence 29 10 2007 1848 1852
32. H. Lee, A. Battle, R. Raina, and A.Y. Ng Efficient sparse coding algorithms Advances in Neural Information Processing Systems 2006
33. M. Aharon, M. Elad, and A. Bruckstein K-svd: an algorithm for designing overcomplete dictionaries for sparse representation IEEE Transactions on Signal Processing 54 11 2006 4311 4322 (Pubitemid 44637761)
34. J. Mairal, M. Elad, and G. Sapiro Sparse representation for color image restoration IEEE Transactions on Image Processing 17 1 2008 53 69
35. J. Wright, A. Yang, A. Ganesh, S. Satry, and Y. Ma Robust face recognition via sparse representation IEEE Transactions on Pattern Analysis and Machine Intelligence 31 2 2009 210 227
36. J. Yang, K. Yu, T. Huang, Supervised translation-invariant sparse coding, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2010.
37. M. Bregonzio, S. Gong, T. Xiang, Recognising action as clouds of space-time interest points, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2009.
38. J. Liu, J. Luo, M. Shah, Recognizing realistic actions from videos in the wild, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2009.
39. A. Gilbert, J. Illingworth, R. Bowden, Fast realistic multi-action recognition using mined dense spatio-temporal feature, in: Proceedings of the IEEE International Conference on Computer Vision, 2010.
40. W. Brendel, S. Todorovic, Activities as time series of human postures, in: Proceedings of European Conference on Computer Vision, 2010.
41. Q. Le, W. Zou, S. Yeung, A. Ng, Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2011.
42. M.D. Rodriguez, J. Ahmed, M. Shah, Action mach: a spatio-temporal maximum average correlation height filter for action recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2008.
43. L. Yeffet, L. Wolf, Local trinary patterns for human action recognition, in: Proceedings of the IEEE International Conference on Computer Vision, 2009.
44. H. Wang, M.M. Ullah, A. Klaser, I. Laptev, C. Schmid, Evaluation of local spatio-temporal features for action recognition, in: Proceedings of the British Machine Vision Conference, 2009.
45. A. Klaser, M. Marszalek, C. Schmid, A spatio-temporal descriptor based on 3D-gradients, in: Proceedings of the British Machine Vision Conference, 2008.
46. A. Fathi, G. Mori, Action recognition by learning mid-level motion features, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2008.
47. H.J. Seo, and P. Milanfar Action recognition from one example IEEE Transactions on Pattern Analysis and Machine Intelligence 33 5 2010 867 882
48. C. Schuldt, I. Laptev, B. Caputo, Recognizing human actions: a local SVM approach, in: Proceedings of International Conference on Pattern Recognition, 2004.
49. M. Blank, L. Gorelick, E. Shechtman, M. Irani, R. Basri, Actions as space-time shapes, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2005.
50. K. Yu, T. Zhang, and Y. Gong Nonlinear learning using local coordinate coding Advances in Neural Information Processing Systems 2009
51. A. Yao, J. Gall, L. Van Gool, A Hough transform-based voting framework for action recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2010.
52. A. Kovashka, K. Grauman, Learning a hierarchy of discriminative space-time neighborhood features for human action recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2010.
53. B. Li, M. Ayazoglu, T. Mao, O. Camps, M. Sznaier, Activity recognition using dynamic subspace angles, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2011.