Acta Optica Sinica, Volume. 34, Issue 12, 1215002(2014)

Human Action Recognition by Leaning Pose Dictionary

Cai Jiaxin1,2、*, Feng Guocan1,2, Tang Xin1,2, and Luo Zhihong3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • show less
    References(36)

    [1] [1] A F Bobick, J W Davis. The recognition of human movement using temporal templates [J]. IEEE Trans Pattern Anal Mach Intell, 2001, 23(3): 257-267.

    [2] [2] T Xiang, S Gong. Beyond tracking: modelling activity and understanding behaviour [J]. International Journal of Computer Vision, 2006, 67(1): 21-51.

    [3] [3] V Chandrashekhar, K Venkatesh. Action energy images for reliable human action recognition [C]. New Delhi: Proc of Asian Symp on Information Display, 2006. 484-487.

    [4] [4] L Wang, D Suter. Informative shape representations for human ction recognition [C]. Hong Kong: 18th International Conference on Pattern Recognition, 2006. 1266-1269.

    [5] [5] D Weinland, R Ronfard, E Boyer. Free viewpoint action recognition using motion history volumes [J]. Computer Vision and Image Understanding, 2007, 104(2-3): 249-257.

    [6] [6] J X Cai, G C Feng, X Tang. Human action recognition using oriented holistic feature [C]. Melbourne: 20th IEEE International Conference on Image Processing, 2013. 2420-2424.

    [7] [7] C Niebles, H C Wang, F F Li. Unsupervised learning of human action categories using spatial-temporal words [J]. International Journal of Computer Vision, 2008, 79(3): 299-318.

    [8] [8] J G Liu, S Ali, M Shah. Recognizing human actions using multiple features [C]. Anchorage: Computer Vision and Pattern Recognition, 2008. 1-8.

    [9] [9] K Alexander, M Marcin, S Cordelia. A spatio-temporal descriptor based on 3D-gradients [C]. Leeds: British Machine Vision Conference, 2008. 995-1004.

    [10] [10] P Scovanner, A Saad, S Mubarak. A 3-dimensional sift descriptor and its application to action recognition [C]. Beijing: Proceedings of the 15th international conference on Multimedia, 2007. 357-360.

    [11] [11] Jin Biao, Hu Wenlong, Wang Hongqi. Moving-objects interaction recognition based on the spatial-temporal semantic information [J]. Acta Optica Sinica, 2012, 32(5): 0515002.

    [12] [12] Zhang Hui, Xu Hui, Lin Liangkui. Super-resolution method of closely spaced objects based on sparse reconstruction using single frame infrared data [J]. Acta Optica Sinica, 2013, 33(4): 0411001.

    [13] [13] Yin Wen, Li Yuanxiang, Zhou Zeming, et al.. Remote sensing image fusion based on sparse representation [J]. Acta Optica Sinica, 2013, 33(4): 0428003.

    [14] [14] Song Lin, Cheng Yongmei, Zhao Yongqiang. Hyper-spectrum classification based on sparse representation model and auto-regressive model [J]. Acta Optica Sinica, 2012, 32(3): 0330003.

    [15] [15] Li Mengjie, Li Jing, Sun Yi. Sparse angular differential phase-contrast computed tomography reconstruction using L1-norm and curvelet constraints [J]. Acta Optica Sinica, 2014, 34(1): 0111003.

    [16] [16] Li Jing, Sun Yi. L1-norm-based differential phase-contrast computerized tomography reconstruction algorithm with sparse angular regolution [J]. Acta Optica Sinica, 2012, 32(3): 0311002.

    [17] [17] T Guha, R Ward. Learning sparse representations for human action recognition [J]. IEEE ransactions on Pattern Analysis and Machine Intelligence, 2012, 34(8): 1576-1588.

    [18] [18] A Castrodad, G Sapiro. Sparse modeling of human actions from motion imagery [J]. International Journal of Computer Vision, 2012, 100(1): 1-15.

    [19] [19] I L Dryden, K V Mardia. Statistical Shape Analysis [M]. New York: John Wiley & Sons Press, 1998. 87-99.

    [21] [21] F Huo, E Hendriks, P Paclik, et al.. Markerless human motion capture and pose recognition [C]. IEEE Workshop on Image Analysis for Multimedia Interactive Services, 2009. 13-16.

    [22] [22] I Leong, J Fang, M Tsai. Automatic body feature extraction from a marker-less scanned human body [J]. Comput-Aided Des, 2007, 39(7): 568-582.

    [23] [23] S Ke, J Hwang, K Lan, et al.. View-invariant 3D human body pose reconstruction using a monocular video camera [C]. IEEE International Conference on Distributed Smart Cameras, 2011. 1-6.

    [24] [24] W Shen, K Deng, X Bai, et al.. Exemplar-based human action pose correction and tagging [C]. IEEE Conference on Computer Vision and Pattern Recognition, 2012. 1784-1791.

    [25] [25] M Y Sang, K Arjan. Human action recognition based on skeleton splitting [J]. Expert Systems with Applications, 2013, 40(17): 6848-6855.

    [26] [26] L Wang, D Suter. Recognizing human activities from silhouettes: motion subspace and factorial discriminative graphical model [C]. IEEE Conference on Computer Vision and Pattern Recognition, 2007. 1-8.

    [27] [27] S Cheema, A Eweiwi, C Thurau, et al.. Action recognition by learning discriminative key poses [C]. IEEE International Conference on Computer Vision Workshops, 2011. 1302-1309.

    [28] [28] A A Chaaraoui, P P Climent, R F Florez. Silhouette-based human action recognition using sequences of key poses [J]. Pattern Recognition Letters, 2013, 34(15): 1799-1807.

    [29] [29] A Veeraraghavan, A K R Chowdhury, R Chellappa. Matching shape sequences in video with applications in human movement analysis [J]. IEEE Transactions Pattern Anal Mach Intell, 2005, 27(12): 1896-1909.

    [30] [30] K Schindler, L V Gool. Action Snippets: How many frames does human action recognition require [C]. Anchorage: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2008. 1-8.

    [31] [31] Y C Pati, R Rezaiifar, P S Krishnaprasad. Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition [C]. IEEE Conference on Signals, Systems and Computers, 1993. 40-44.

    [32] [32] R Rubinstein, T Peleg, M Elad. Analysis K-SVD: A dictionary-learning algorithm for the analysis sparse model [J]. IEEE Transactions on Signal Processing, 2013, 61(3): 661-677.

    [34] [34] B Mosh, G Lena, S Eli, et al.. Actions as space-time shapes [C]. IEEE International Conference on Computer Vision, 2005. 1395-1402.

    [35] [35] Q Zhao, H S Horace. Unsupervised approximate-semantic vocabulary learning for human action and video classification [J]. Pattern Recognition Letters, 2013, 34(15): 1870-1878.

    [36] [36] S Singh, S Velatin, H Ragheb. MuHAVi: A multicamera human action video dataset for the evalution of action recognition methods [C]. IEEE International Conference on Adavanced Video and Signal Based Surveillance, 2010. 48-55.

    CLP Journals

    [1] Yan Limin, Du Bin, Pan Hao, Guo Qiang. Recognition of Three-Dimensional Dynamic Finger Gesture Based on Leap Motion[J]. Laser & Optoelectronics Progress, 2016, 53(11): 111001

    [2] Qiu Lida, Fu Ping, Lin Nan, Zhang Ning. Discriminative Low-Rank Projection Dictionary Pair Learning[J]. Laser & Optoelectronics Progress, 2016, 53(11): 111003

    [3] Haiyang Xu, Jun Kong, Min Jiang, Baofeng Zan. Action Recognition Based on Histogram of Spatio-Temporal Oriented Principal Components[J]. Laser & Optoelectronics Progress, 2018, 55(6): 061009

    [4] Haiyang Xu, Jun Kong, Min Jiang. Human Action Recognition Based on Quaternion 3D Skeleton Representation[J]. Laser & Optoelectronics Progress, 2018, 55(2): 021002

    Tools

    Get Citation

    Copy Citation Text

    Cai Jiaxin, Feng Guocan, Tang Xin, Luo Zhihong. Human Action Recognition by Leaning Pose Dictionary[J]. Acta Optica Sinica, 2014, 34(12): 1215002

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Machine Vision

    Received: Apr. 3, 2014

    Accepted: --

    Published Online: Nov. 4, 2014

    The Author Email: Jiaxin Cai (caijxin@mail2.sysu.edu.cn)

    DOI:10.3788/aos201434.1215002

    Topics