Learning sparse representations for human action recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 34, Issue 8, 2012, Pages 1576-1588

  Guha, Tanaya ^a   Ward, Rabab K ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

Action recognition; dictionary learning; expression recognition; orthogonal matching pursuit; overcomplete; sparse representation; spatio temporal descriptors

Indexed keywords

ACTION RECOGNITION; DESCRIPTORS; DICTIONARY LEARNING; EXPRESSION RECOGNITION; ORTHOGONAL MATCHING PURSUIT; OVER-COMPLETE; SPARSE REPRESENTATION;

GESTURE RECOGNITION; IMAGE RECOGNITION; VECTOR QUANTIZATION; VIDEO RECORDING;

MOTION ESTIMATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; DANCING; FACIAL EXPRESSION; FACTUAL DATABASE; HUMAN; IMAGE PROCESSING; METHODOLOGY; MOVEMENT (PHYSIOLOGY); NOMENCLATURE; SPORT; THEORETICAL MODEL; VIDEORECORDING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DANCING; DATABASES, FACTUAL; FACIAL EXPRESSION; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MODELS, THEORETICAL; MOVEMENT; PATTERN RECOGNITION, AUTOMATED; SPORTS; TERMINOLOGY AS TOPIC; VIDEO RECORDING;

EID: 84862649818     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2011.253     Document Type: Article

References (36)

1. B. Wohlberg, "Noise Sensitivity of Sparse Signal Representations: Reconstruction Error Bounds for the Inverse Problem," IEEE Trans. Signal Processing, vol. 51, no. 12, pp. 3053-3060, Dec. 2003.
2. J. Wright, A.Y. Yang, A. Ganesh, S.S. Sastry, and Y. Ma, "Robust Face Recognition via Sparse Representation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 31, no. 2, pp. 210-227, Feb. 2008.
3. M.S. Lewicki and T.J. Sejnowski, "Learning Overcomplete Representations," Neural Computation, vol. 12, no. 2, pp. 337-365, 2000.
4. K. Engan, S.O. Aase, and J.H. Husoy, "Method of Optimal Directions for Frame Design," Proc. IEEE Int'l Conf. Audio, Speech and Signal Processing, 1999.
5. M. Aharon, M. Elad, and A. Bruckstein, "K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation," IEEE Trans. Signal Processing, vol. 54, no. 11, pp. 4311-4322, Nov. 2006. (Pubitemid 44637761)
6. J. Mairal, M. Elad, and G. Sapiro, "Sparse Representation for Color Image Restoration," IEEE Trans. Image Processing, vol. 17, no. 1, pp. 53-69, Jan. 2008.
7. M. Elad and M. Aharon, "Image Denoising via Sparse and Redundant Representations over Learned Dictionaries," IEEE Trans. Image Processing, vol. 15, no. 12, pp. 3736-3745, Dec. 2006. (Pubitemid 44811686)
8. P. Dollar, V. Rabaud, G. Cottrell, and S. Belongie, "Behavior Recognition via Sparse Spatio-Temporal Features," Proc. Second IEEE Joint Int'l Workshop Visual Surveillance and Performance Evaluation of Tracking and Surveillance, pp. 65-72, Oct. 2005. (Pubitemid 46178025)
9. L. Gorelick, M. Blank, E. Shechtman, M. Irani, and R. Basri, "Actions as Space-Time Shapes," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 29, no. 12, pp. 2247-2253, Dec. 2007. (Pubitemid 350124072)
10. Y. Wang and G. Mori, "Human Action Recognition by Semilatent Topic Models," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 31, no. 10, pp. 1762-1774, Oct. 2009.
11. M. Rodriguez, J. Ahmed, and M. Shah, "Action Match a Spatio-Temporal Maximum Average Correlation Height Filter for Action Recognition," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, June 2008.
12. G. Peyré, "Sparse Modeling of Textures," J. Math. Imaging and Vision, vol. 34, no. 1, pp. 17-31, 2009.
13. J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman, "Discriminative Learned Dictionaries for Local Image Analysis," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
14. J. Yang, K. Yu, Y. Gong, and T. Huang, "Linear Spatial Pyramid Matching Using Sparse Coding for Image Classification," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1794-1801, 2009.
15. Y. Zhu, X. Zhao, Y. Fu, and Y. Liu, "Sparse Coding on Local Spatial-Temporal Volumes for Human Action Recognition," Proc. 10th Asian Conf. Computer Vision, vol. 6493, pp. 660-671, 2010.
16. I. Laptev, "On Space-Time Interest Points," Int'l J. Computer Vision, vol. 64, pp. 107-123, 2005. (Pubitemid 41314645)
17. P. Scovanner, S. Ali, and M. Shah, "A 3-Dimensional Sift Descriptor and Its Application to Action Recognition," Proc. 15th Int'l Conf. Multimedia, pp. 357-360, 2007.
18. A.A. Efros, A.C. Berg, G. Mori, and J. Malik, "Recognizing Action at a Distance," Proc. Ninth IEEE Int'l Conf. Computer Vision, 2003.
19. F. Jurie and B. Triggs, "Creating Efficient Codebooks for Visual Recognition," Proc. 10th IEEE Int'l Conf. Computer Vision, 2005.
20. H. Wang, M.M. Ullah, A. Klaser, I. Laptev, and C. Schmid, "Evaluation of Local Spatio-Temporal Features for Action Recognition," Proc. British Machine Vision Conf., Sept. 2009.
21. J. Niebles, H. Wang, and L. Fei-Fei, "Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words," Int'l J. Computer Vision, vol. 79, pp. 299-318, 2008.
22. I.N. Junejo, E. Dexter, I. Laptev, and P. Perez, "View-Independent Action Recognition from Temporal Self-Similarities," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 33, no. 1, pp. 172-185, Jan. 2011.
23. A.F. Bobick and J.W. Davis, "The Recognition of Human Movement Using Temporal Templates," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 3, pp. 257-267, Mar. 2001. (Pubitemid 32286632)
24. D.G. Lowe, "Distinctive Image Features from Scale-invariant Keypoints," Int'l J. Computer Vision, vol. 60, pp. 91-110, 2004.
25. R. Baraniuk and M. Wakin, "Random Projections of Smooth Manifolds," Foundations of Computational Math., vol. 9, pp. 51-77, 2009.
26. M.A. Fischler and R.C. Bolles, "Random Sample Consensus: a Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography," Comm. ACM, vol. 24, pp. 381-395, June 1981.
27. Y. Eldar and H. Bolcskei, "Block-Sparsity: Coherence and Efficient Recovery," Proc. IEEE Int'l Conf. Acoustics, Speech, and Signal Processing, pp. 2885-2888, 2009.
28. C. Schmid, R. Mohr, and C. Bauckhage, "Evaluation of Interest Point Detectors," Int'l J. Computer Vision, vol. 37, pp. 151-172, 2000.
29. L. Yeffet and L. Wolf, "Local Trinary Patterns for Human Action Recognition," Proc. IEEE Int'l Conf. Computer Vision, pp. 492-497, Oct. 2009.
30. M.D. Hayko Riemenschneider and H. Bischof, "Bag of Optical Flow Volumes for Image Sequence Recognition," Proc. British Machine Vision Conf., 2009.
31. S. Ali and M. Shah, "Human Action Recognition in Videos Using Kinematic Features and Multiple Instance Learning," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 32, no. 2, pp. 288-303, Feb. 2010.
32. C. Thurau and V. Hlavac, "Pose Primitive Based Human Action Recognition in Videos or Still Images," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2008.
33. Z. Zhang, Y. Hu, S. Chan, and L.-T. Chia, "Motion Context: A New Representation for Human Action Recognition," Proc. European Conf. Computer Vision, vol. 5305, pp. 817-829, 2008.
34. A. Fathi and G. Mori, "Action Recognition by Learning Mid-Level Motion Features," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2008.
35. A. Yao, J. Gall, and L. Van Gool, "A Hough Transform-based Voting Framework for Action Recognition," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 2061-2068, June 2010.
36. A. Kovashka and K. Grauman, "Learning a Hierarchy of Discriminative Space-Time Neighborhood Features for Human Action Recognition," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 2046-2053, June 2010.