Human movement analysis around a view circle using time-order similarity distributions

Chi-Hung Chuang1, Jun-Wei Hsieh2, Hui-Fen Chiang2, Yi-Da Chiou3
1Dept. of Learning and Digital Technology, Fo Guang University, No. 160, Linwei Rd., Jiaosi, Yilan 26247, Taiwan
2Dept. of Computer Science and Engineering, National Taiwan Ocean University, No.2, Beining Rd., Keelung 202, Taiwan
3Department of Electrical Engineering, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li 320, Taiwan

Tài liệu tham khảo

Weinland, 2011, A survey of vision-based methods for action representation, segmentation, and recognition, Comput. Vision Image Understand., 115, 224, 10.1016/j.cviu.2010.10.002 Poppe, 2010, A survey on vision-based human action recognition, Image Vision Comput., 28, 976, 10.1016/j.imavis.2009.11.014 D. Weinland, E. Boyer, Action recognition using exemplar-based embedding, in: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 2008, pp. 1–7. D. Weinland, E. Boyer, R. Ronfard, Action recognition from arbitrary views using 3D exemplars, in: International Conference on Computer Vision, June 2007, pp. 1–7. D. Weinland, R. Ronfard, E. Boyer, Automatic discovery of action taxonomies from multiple views, in: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, 2006, pp. 1639–1645. A. Fathi, G. Mori, Action recognition by learning mid-level motion features, in: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 2008, pp. 1–8. S. Ju et al., Hierarchical spatio-temporal context modeling for action recognition, in: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 2009, pp. 2004–2011. J.-X. Wu et al., A scalable approach to activity recognition based on object use, in: International Conference on Computer Vision, October 2007, pp. 1–8. H. Meng, N. Pears, C. Bailey, A human action recognition system for embedded computer vision, in: IEEE Conference on Computer Vision and Pattern Recognition, June 2007, pp. 1–6. L. Kratz, K. Nishino, Anomaly detection in extremely crowded scenes using spatio-temporal motion pattern models, in: IEEE Conference on Computer Vision and Pattern Recognition, 2009, pp. 1446–1453. A. Gaidon, Z. Harchaoui, C. Schmid, Actom sequence models for efficient action detection, in: IEEE Conference on Computer Vision and Pattern Recognition, 2011. B. Yao, L. Fei-Fei, Grouplet: a structure image representation for recognizing human and object interactions, in: IEEE International Conference on Computer Vision and Pattern Recognition, 2010. S. Maji, L. Bourdev, J. Malik, Action recognition from a distributed representation of pose and appearance, in: IEEE Conference on Computer Vision and Pattern Recognition, 2011. G. Shakhnarovich, P. Viola, T. Darrell, Fast pose estimation with parameter-sensitive hashing, in: International Conference on Computer Vision, 2003, pp. 750–757. A.O. Balan et al., Detailed human shape and pose from images, in: IEEE Conference On Computer Vision and Pattern Recognition, June 2007, pp. 1–8. A. Farhadi, M.K. Tabrizi, Learning to recognize activities from the wrong view point, in: Proceedings of the 10th European Conference on Computer Vision, 2008, pp. 154–166. A. Farhadi, M.K. Tabrizi, I. Endres, D. Forsyth, A latent model of discriminative aspect, in: International Conference on Computer Vision, 2009, pp. 948–955. F. Lv, R. Nevatia, Single view human action recognition using key pose matching and Viterbi path searching, in: IEEE Conference on Computer Vision and Pattern Recognition, June 2007, pp. 1–8. K. Grauman, T. Darrell, The pyramid match kernel: discriminative classification with sets of image features, in: International Conferencer on Computer Vision, vol. 2, October 2005, pp. 1458–1465. L.R. Rabiner, A tutorial on Hidden Markov models and selected applications in speech recognition, in: Proceedings of the IEEE, vol. 77, no. 2, February 1989, pp. 257–286. R. Souvenir, J. Babbs, Learning the viewpoint manifold for action recognition, in: IEEE Conference on Computer Vision and Pattern Recognition, 2008, pp. 1–7. Junejo, 2011, View-independent action recognition from temporal self-similarities, IEEE Trans. Pattern Recogn. Machine Intell., 33, 172, 10.1109/TPAMI.2010.68 F. Cuzzolin, Using bilinear models for view-invariant action and identity recognition, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, 2006, pp. 1701–1708. S. Karthikeyan, U. Gaur, B.S. Manjunath, Probabilistic subspace-based learning of shape dynamics modes for multi-view action recognition, in: IEEE International Conference on Computer Vision, 2011. C.S. Lee, A. Elgamma, Modeling view and posture manifolds for tracking, in: International Conference on Computer Vision, October 2007, pp. 1–8. P.-K. Yan, S.M. Khan, M. Shah, Learning 4D action feature models for arbitrary view action recognition, in: IEEE Conference on Computer Vision and Pattern Recognition, June 2008, pp. 1–7. Hsieh, 2008, Video-based human movement analysis and its application to surveillance systems, IEEE Trans. Multimedia, 10, 372, 10.1109/TMM.2008.917403 Belongie, 2002, Shape matching and object recognition using shape contexts, IEEE Trans. Pattern Recogn. Machine Intell., 24, 509, 10.1109/34.993558 Y. Wang, K. Huang, T. Tan, Human activity recognition based on R transform, in: IEEE Conference on Computer Vision and Pattern Recognition, 2007. S. Kullback, Information theory and statistics, Dover Books on Mathematics, July 1997. Anguelov, 2005, SCAPE: shape completion and animation of people, ACM Trans. Graphics, 24, 408, 10.1145/1073204.1073207 R. Gross, J. Shi, The CMU motion of body (MoBo) database, Technical Report CMU-RI-TR-01-18, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, June 2001.