Human Action Recognition Algorithm Based on Selective Ensemble Rotation Forest
TANG Chao1, WANG Wenjian2, LI Wei3 , LI Guobin1, CAO Feng2, ZHANG Miaohui4
1.Department of Computer Science and Technology, Hefei University, Hefei 230601 2.School of Computer and Information Technology, Shanxi University, Taiyuan 030006 3.College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361005 4.Energy Research Institute, Jiangxi Academy of Sciences, Nanchang 330096
Abstract：The representation of high dimensional human actions and the construction of accurate and stable human classification model are key issues in human action recognition. An efficient action recognition algorithm based on mixed features is proposed. Key joints of human body polar coordinates features based on appearance structure and motion features based on optical flow are fused into the proposed algorithm to capture motion information in video sequences and improve the recognition instantaneity. Meanwhile, the selective ensemble rotation forest model (SERF) based on frame is developed and the selection ensemble strategy is used to select the base classifier of rotation forest and increase differences among the classifiers. Experimental results show the better classification accuracy and robustness of the proposed model.
唐超，王文剑，李伟，李国斌，曹峰，张苗辉. 基于选择性集成旋转森林的人体行为识别算法*[J]. 模式识别与人工智能, 2016, 29(4): 313-321.
TANG Chao, WANG Wenjian, LI Wei , LI Guobin, CAO Feng, ZHANG Miaohui. Human Action Recognition Algorithm Based on Selective Ensemble Rotation Forest. , 2016, 29(4): 313-321.
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2016, Vol. 29 
