Conclusions and Future Work
5.2 Future work
5.2 Future work
Since the CSC descriptor for human posture is not a view-invariant representation, we can not deal with same atomic actions with different views. Therefore, we shall handle this problem to make our system more scalable in the future.
Moreover, high-level semantic description for human action using natural language will be another subject for our future work.
85
-Bibliography
[1] J. K. Aggarwal and Q. Cai, “Human motion analysis: a review,” Computer Vision and Image Understanding, Vol. 73, No. 3, pp. 428- 440, 1999.
[2] A. Ali and J. K. Aggarwal, “Segmentation and recognition of continuous human activity,” Proceedings of IEEE Workshop on Detection and Recognition of Events in Video, pp. 28- 35, 2001.
[3] M. Blank, L. Gorelick, E. Shechtman, M. Irani, and R. Barsi, “Actions as space-time shapes,” Proceedings of the IEEE International Conference on Computer Vision, Vol. 2, pp. 1395- 1402, 2005.
[4] H.A. Baler Saip and C.L. Lucchesi, “Matching algorithm for bipartite graph,” Technical Report DCC-03/93, Departamento de Cincia da Computao, Universidade Estudal de Campinas, 1993.
[5] S. Belongie, J. Malik, and J. Puzicha, “Shape matching and object recognition using shape contexts,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 24, pp. 509- 522, 2002.
- 87 -
[6] M. Belkin and P. Niyogi, “Laplacian eigenmaps for dimensionality reduction and data representation,” Neural Computation, Vol. 15, No. 6, pp. 1373- 1396, 2003.
[7] A. F. Bobick and Y. A. Invanov, “Action recognition using probabilistic parsing,” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 192- 202, Santa Barbara, California, 1998.
[8] A. F. Bobick and J. W. Davis, “The recognition of human movement using temporal templates,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 3, pp. 257- 267, 2001.
[9] B. Boulay, F. Bremond, and M. Thonnat, “Human posture recognition in video sequence,” Proceedings IEEE Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, pp. 23- 29, 2003.
[10] M. Broniatowski, “Estimation of the Kullback-Leibler Divergence,”
Mathematical Methods of Statistics, 2003.
[11] D. Y. Chen, S. W. Shih, and H. Y. Mark Liao, “Atomic human action segmentation using a spatio-temporal probabilistic,” Proceedings of IEEE International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 327- 330, Pasadena, CA, USA, Dec. 2006.
[12] T. J. Chin, L. Wang, K. Schindler, and D. Suter, “Extrapolating learned manifolds for human activity recognition,” Proceedings of the IEEE
Bibliography
International Conference on Image Processing, Vol. 1, pp. 381- 384, 2007.
[13] K. D. Cock and B. D. Moor, “Subspace anagles and distances between ARMA models,” Proceedings of the Mathematical Theory of Networks and Systems, 2000.
[14] R. T. Collins, A. J. Lipton, and T. Kanade, “Introduction to the special section on video surveillance,” IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 22, No. 8, pp. 745- 746, 2000.
[15] T. F. Cox and M.A.A Cox, Multidimensional Scaling. Chapman and Hall, 2001.
[16] W. B. Croft and J. Lafferty, Language Modeling for Information Retrieval, Kluwer Academic Publishers, Norwell, MA, 2003.
[17] N. P. Cuntoor and R. Chellappa, “Key frame-based activity representation using antieigenvalues,” ACCV 2006, LNCS 3852, pp. 499- 508, 2006.
[18] I. S. Dhillon, “Co-clustering documents and words using bipartite spectral graph partitioning,” Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 269-274, 2001.
[19] S. L. Dockstader, M. J. Berg, and A. M. Tekalp, “Stochastic kinematic modeling and feature extraction for gait analysis,” IEEE Transactions on Image Processing, Vol. 12, No. 8, pp. 962-976, 2003.
89
-[20] A. Elgammal and C. S. Lee, “Inferring 3D body pose from silhouettes using activity manifold learning,” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2, pp. 681- 688, 2004.
[21] W. Freeman, K. Tanaka, J. Ohta, and K. Kyuma, “Computer vision for computer games,” Proceedings of IEEE International Conference on Automatic Face and Gesture Recognition, pp. 100-105, 1996.
[22] A. Galata, N. Johnson, and D. Hogg, “Learning variable-length Markov models of behavior,” Computer Vision and Image Understanding,” Vol. 81, No. 3, pp. 398- 413, 2001.
[23] D. M. Gavrila, “The visual analysis of human movement: a survey,”
Computer Vision and Image Understanding, Vol. 73, No. 1, pp. 82- 98, 1999.
[24] P. Guttorp, Stochastic Modeling of Scientific Data, London: Chapman and Hall/CRC, 1995.
[25] I. Guyon and F. Pereira, “Design of a linguistic postprocessor using variable memory length Markov models,” Proceedings of International Conference on Document Analysis and Recognition, pp. 454- 457, Montréal, Canada, 1995.
[26] I. Haritaoglu, D. Harwood, and L. S. Davis, “W4: real-time surveillance of people and their activities,” IEEE Transactions on Pattern Analysis and
Bibliography
Machine Intelligence, Vol. 22, No. 8, 2000.
[27] J. W. Hsieh, Y. T. Hsu, H. Y. Mark Liao and C. C. Chen, “Video-based human movement analysis and its application to surveillance systems,” IEEE Transactions on Multimedia, Vol. 10, pp. 372- 384, 2008.
[28] J. E. Hunter, D. M. Wilkes, D. T. Levin, C. Heaton, and M. M. Saylor,
“Autonomous segmentation of human action for behaviour analysis,”
Proceedings of IEEE International Conference on Development and Learning, Monterery, California, Aug. 2008.
[29] A. K. Jain, M. N. Murthy, and P. J. Flynn, “Data clustering: a review,” ACM Computing Surveys, Vol. 31, pp. 264- 323, 1999.
[30] F. Jelinek, Statistical Methods for Speech Recognition, Cambridge, Mass.:
MIT Press, 1998.
[31] I. T. Jolliffe, Principal Component Analysis. Springer, 1989.
[32] R. Kuhn and R. De Mori, “A cache-based natural language model for speech recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 12, No. 6, pp. 570- 583, 1990.
[33] Martin H. C. Law and Anil K. Jain, “Incremental nonlinear dimensionality reduction by manifold learning,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, No. 3, 2006.
91
-[34] H. Li, S. Lin, Y. Zhang, and K. Tao, “Automatic video-based analysis of athlete action,” Proceedings of IEEE International Conference on Image Analysis and Processing, pp. 205- 210, Modena, Italy, Sep. 2007.
[35] Y. Li, S. Ma, and H. Lu, “Human posture recognition using multi-scale morphological method and Kalman motion estimation,” Proceedings of IEEE International Conference on Pattern Recognition, pp. 175-177, 1998.
[36] T. Lin and H. Zha, “Riemannian manifold learning,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 30, No. 5, 2008.
[37] F. Lv and R. Nevatia, “Single view human action recognition using key pose matching and viterbi path searching,” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1- 8, Minneapolis, Minnesota, June 2007.
[38] H. Meng, N. Pears, and C. Bailey, “A human action recognition system for embedded computer vision application,” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, Minnesota, June 2007.
[39] H. Miyamori and S. Iisaku, “Video annotation for content-based retrieval using human behavior analysis and domain knowledge,” Proceedings of IEEE International Conference on Automatic Face and Gesture Recognition, pp. 320- 325, Grenoble, France, 2000.
Bibliography
[40] T. Moeslund and E. Granum, “A survey of computer vision-based human motion capture,” Computer Vision and Image Understanding, Vol. 81, No. 3, pp. 231- 268, 2001.
[41] V. I. Morariu and O. I. Camps, “Modeling correspondences for multi-camera tracking using nonlinear manifold learning and target dynamics,”
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 1, pp. 545- 552, 2006.
[42] T. Nakata, “Temporal segmentation and recognition of body motion data based on inter-limb correlation analysis,” Proceedings of IEEE International Conference on Intelligent Robots and Systems, San Diego, CA, USA, 2007.
[43] C. G. Nevill-Manning and I. H. Witten, “On-line and off-line heuristics for inferring hierarchies of repetitions in sequence,” Proceedings of the IEEE, Vol. 88, No. 11, 2000.
[44] A. S. Ogale, A. Karapurkar, and Y. Aloimonos, “View-invariant modeling and recognition of human actions using grammars,” Workshop on Dynamical Vision at ICCV, Beijing, China, 2005.
[45] J. Ohya, “Analysis of human behaviors by computer vision based approaches,” Proceedings of IEEE International Conference on Multimedia and Expo, Vol. 1, pp. 913- 916, Lusanne, Switzerland, Aug. 2002.
[46] J. Park, S. Park, and J. K. Aggarwal, “Model-based human motion tracking
93
-and behavior recognition using hierarchical finite state automata,”
Proceedings of International Conference on computational Science and Its Applications, pp. 311- 320, Assisi, Italy, 2004.
[47] R. Plamondon and S. N. Srihari, “Online and off-line handwriting recognition: a comprehensive survey,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 1, pp. 63- 84, 2000.
[48] Y. Qiao and M. Yasuhara, “Affine invariant dynamic time warping and its applications to online rotated handwriting recognition,” Proceedings of the IEEE International Conference on Pattern Recognition, Vol. 2, pp. 905- 908, 2006.
[49] L. R. Rabiner, “A tutorial on hidden Markov models and selected applications in speech recognition,” Proceedings of the IEEE, Vol. 77, No. 2, 1989.
[50] M. M. Rahman and S. Ishikawa, “Robust appearance-based human action recognition,” Proceedings of IEEE International Conference on Pattern Recognition, Vol. 3, pp. 165- 168, Cambridge, UK, Aug. 2004.
[51] N. Rane and S. Birchfield, “Isomap tracking with particle filtering,”
Proceedings of the IEEE International Conference on Image Processing, Vol.
2, pp. 513- 516, 2007.
[52] D. Ron, Y. Singer, and N. Tishby, “The power of amnesia,” Advances in
Bibliography
Neural Information Processing Systems, pp. 176- 183, Morgan Kauffmann, New York, 1994.
[53] R. Rosenfeld, “Two decades of statistical language modeling: where do we go from here,” Proceedings of the IEEE, Vol. 88, No. 8, pp. 1270- 1278, 2000.
[54] S. T. Roweis and L. K. Saul, “Nonlinear dimensionality reduction by locally linear embedding,” Science, Vol. 290, pp. 2323- 2326, 2000.
[55] R. Sharma, V. I. Pavlović, and T. S. Huang, “Toward multimodal human-computer interface,” Proceedings of the IEEE, Vol. 86, No. 5, pp.
853- 869, 1998.
[56] D. Shen and H. H. S. Ip, “Discriminative wavelet shape descriptors for recognition of 2-D patterns,” Pattern Recognition, Vol. 32, pp. 151- 165, 1999.
[57] C. W. Su, H. Y. Mark Liao, H. R. Tyan, C. W. Lin, D. Y. Chen, and K. C. Fan,
“Motion flow-based video retrieval,” IEEE Transactions on Multimedia, Vol.
9, No. 6, pp. 1193- 1201, 2007.
[58] J. B. Tenenbaum, V. de Silva, and J. C. Langford, “A global geometric framework for nonlinear dimensionality reduction,” Science, Vol. 290, pp.
2319- 2323, 2000.
[59] P. K. Turaga, A. Veeraraghavan, and R. Chellappa, “From videos to verbs:
95
-mining videos for activities using a cascade of dynamical systems, ＂ Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1- 8, 2007.
[60] M. Turk and A. Pentland, “Eigenfaces for recognition,” Journal of Cognitive Neuroscience, Vol. 3, No. 1, pp. 71- 86, 1991.
[61] A. Vinciarelli, S. Bengio, and H. Bunke, “Offline recognition of unconstrained handwritten texts using HMMs and statistical language models,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 6, pp. 709- 720, 2004.
[62] L. Wang and D. Suter, “Learning and matching of dynamic shape manifolds for human action recognition,” IEEE Transactions on Image Processing, Vol.
16, No. 6, 2007.
[63] L. Wang and D. Suter, “Informative shape representations for human action recognition,” Proceedings of the IEEE International Conference on Pattern Recognition, Vol. 2, pp. 1266- 1269, 2006.
[64] L. Wang, W. Hu, and T. Tan, “Recent developments in human motion analysis,” Pattern Recognition, Vol. 36, No. 3, pp. 585- 601, 2003.
[65] T. S. Wang, H. Y. Shum, Y. Q. Xu, and N. N. Zheng, “Unsupervised analysis of human gestures,” Proceedings of the IEEE Pacific-Rim Conference on Multimedia, pp. 174- 181, 2001.
Bibliography
[66] N. Werghi, “A discriminative 3D wavelet-based descriptors: application to the recognition of human body postures,” Pattern Recognition Letters, Vol.
26, pp. 663- 677, 2005.
[67] C. R. Wren, A. Azarbayejani, T. Darrell, and A. P. Pentland, “Pfinder:
real-time tracking of the human body,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, No. 7, pp. 780- 785, 1997.
[68] M. Yazdi, A. B. Albu, and R. Bergevin, “Morphological analysis of spatio-temporal patterns for the segmentation of cyclic human activities,”
Proceedings of IEEE International Conference on Pattern Recognition, Vol.
4, pp. 240- 243, Combridge, UK, Aug. 2004.
[69] J. Yamato, J. Ohya, and K. Ishii, “Recognizing human action in time-sequential images using hidden Markov model,” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 379- 385, 1992.
[70] J. Yang, Y. Xu, and C. S. Chen, “Human action learning via hidden Markov model,” IEEE Transactions on System, Man, and Cybernetics, Vol. 27, No. 1, pp. 34- 44, 1997.
[71] C. Zhai and J. Lafferty, “A study of smoothing methods for language models applied to information retrieval,” ACM Transactions on Information Systems, Vol. 22, No. 2, pp. 179- 214, 2004.
97
-[72] H. Zhong, J. Shi, and M. Visontai, “Detecting unusual activity in video,”
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2, pp. 819- 826, 2004.
[73] http://en.wikipedia.org/wiki/Statistical_significance.
Publication List