[1] Li Hongsong, Li Da. Some advances in human motion analysis [J]. PR&AI, 2009, 22(1): 70-78.
[2] Xu Guangyou, Cao Yuanyuan. Action recognition and activity understanding: a review [J]. Journal of Image and Graphics, 2009, 14(2): 189-195.
[3] A F Bobick, J W Davis. The recognition of human movement using temporal templates [J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2001, 23(3): 257-267.
[4] D Weinland, R Ronfard, E Boyer. Free viewpoint action recognition using motion history volumes [J]. Computer Vision and Image Understanding, 2006, 104(2-3): 249-257.
[5] J X Cai, G C Feng, X Tang. Human action recognition using oriented holistic feature [C]. 20th IEEE International Conference on Image Processing, 2013. 2420-2424.
[9] 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.
[10] J C Niebles, H C Wang, F F Li. Unsupervised learning of human action categories using spatial-temporal words [J]. Int J Comput Vis, 2008, (79): 299-318.
[11] K Alexander, M Marcin, S Cordelia. A spatio-temporal descriptor based on 3d-gradients [C]. British Machine Vision Conference, IEEE Computer Society, 2008. 995-1004.
[12] S Poul, A Saad, S Mubarak. A 3-dimensional sift descriptor and its application to action recognition [C]. Proceedings of the 15th international conference on Multimedia, IEEE Computer Society, 2007. 357-360.
[13] Haihua Cui, Wenhe Liao, Ning Dai, et al.. Registration and integration algorithm in structured light three-dimensional scanning based on scale-invariant feature matching of multi-source images [J]. Chin Opt Lett, 2012, 10(9): 091001.
[14] Jianfang Dou, Jianxun Li. Robust image matching based on SIFT and delaunay triangulation [J]. Chin Opt Lett, 2012, 10(s1): s11001.
[15] Mingliang Gao, Xiaomin Yang, Yanmei Yu, et al.. Photometric invariant feature descriptor based on SIFT [J]. Chin Opt Lett, 2012, 10(s1): s11003.
[16] J G Liu, S Ali, M Shah. Recognizing human actions using multiple features [C]. Computer Vision and Pattern Recognition, IEEE Computer Society, 2008. 1-8.
[17] J Yamato, J Ohya, K Ishii. Recognizing human action in time sequential images using hidden Markov model[C]. IEEE Conference on Computer Vis Pattern Recognit, 1992. 379-385.
[18] M Brand, N Oliver, A Pentland. Coupled hidden Markov models for complex action recognition [C]. IEEE Conference on Computer Vis Pattern Recognit, 1997: 994-999.
[19] Q F Shi, L Wang, L Cheng, et al.. Discriminative human action segmentation and recognition using semi-markov model [C]. IEEE Comference on Computer Vision and Pattern Recognition, 2008: 1-5.
[20] C Sminchisescu, A Kanaujia, D Metaxax. Conditional models for contextual human motion recognition [J]. Computer Vision and Jmago Understanding, 2006, 104(2-3): 210-220.
[21] L Wang, D Suter. Visual learning and recognition of sequential data manifolds with applications to human movement analysis [J]. Computer Vision and Image Understanding, 2008, 110(2): 153-172.
[22] 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.
[23] C A Andre, C P Pau, Flórez-Revuelta Francisco. Silhouette-based human action recognition using sequences of key poses [J]. Pattern Recognition Letters, 2013, 34(15): 1799-1807.
[25] S Suzuki, K Be. Topological structural analysis of digitized binary images by border following[J]. Comput Vision Graphics Image Process, 1985, 30(1): 32-46.
[26] H T Kam. The random subspace method for constructing decision forests [J]. Pattern Analysis and Machine, 1998, 20(8): 832-844.
[27] B Leo. Random Forests [J]. Machine Learning, 2001, 45(1): 5-32.
[28] Zhang Hongqiang, Liu Guangyuan, Lai Xiangwei. Application of random forest algorithm in important feature selection from EMG signal [J]. Computer Science, 2013, 40(1): 200-202.
[29] Guo Jinxin, Chen Wei. Face recognition based on HOG multi-feature fusion and random forest [J]. Computer Science, 2013, 40(10): 279-282.
[30] Haixia Xu, Xianbin Wen, Yongliao Zou, et al.. Performance evaluation and segmentation for synthetic aperture radar image using mixture multiscale autoregressive model and bootstrap technique [J]. Chin Opt Lett, 2012, 10(s1): s11005.
[31] B Mosh, G Lena, S Eli, et al.. Actions as space-time Shapes [C]. IEEE International Conference on Computer Vision, 2005, 2: 1395-1402.
[32] 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.
[33] 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 Boston: Adavanced Video and Signal Based Surveillance(AVSS), 2010. 48-55.