Learning Discriminative Key Poses for Action Recognition | |
Liu, Li1; Shao, Ling1,2; Zhen, Xiantong1; Li, Xuelong3![]() | |
刊名 | ieee transactions on cybernetics
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2013-12-01 | |
卷号 | 43期号:6页码:1860-1870 |
关键词 | AdaBoost computer vision extensive pyramidal features (EPFs) human action recognition pose selection weighted local naive Bayes nearest neighbor (WLNBNN) classifier |
英文摘要 | in this paper, we present a new approach for human action recognition based on key-pose selection and representation. poses in video frames are described by the proposed extensive pyramidal features (epfs), which include the gabor, gaussian, and wavelet pyramids. these features are able to encode the orientation, intensity, and contour information and therefore provide an informative representation of human poses. due to the fact that not all poses in a sequence are discriminative and representative, we further utilize the adaboost algorithm to learn a subset of discriminative poses. given the boosted poses for each video sequence, a new classifier named weighted local naive bayes nearest neighbor is proposed for the final action classification, which is demonstrated to be more accurate and robust than other classifiers, e.g., support vector machine (svm) and naive bayes nearest neighbor. the proposed method is systematically evaluated on the kth data set, the weizmann data set, the multiview ixmas data set, and the challenging hmdb51 data set. experimental results manifest that our method outperforms the state-of-the-art techniques in terms of recognition rate. |
WOS标题词 | science & technology ; technology |
类目[WOS] | computer science, artificial intelligence ; computer science, cybernetics |
研究领域[WOS] | computer science |
关键词[WOS] | wavelet transform ; classification ; regression ; features ; points |
收录类别 | SCI ; EI |
语种 | 英语 |
WOS记录号 | WOS:000327647500029 |
公开日期 | 2015-06-30 |
内容类型 | 期刊论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/23438] ![]() |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
作者单位 | 1.Univ Sheffield, Dept Elect & Elect Engn, Sheffield S1 3JD, S Yorkshire, England 2.Nanjing Univ Informat Sci & Technol, Coll Elect & Informat Engn, Nanjing 210044, Jiangsu, Peoples R China 3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Peoples R China |
推荐引用方式 GB/T 7714 | Liu, Li,Shao, Ling,Zhen, Xiantong,et al. Learning Discriminative Key Poses for Action Recognition[J]. ieee transactions on cybernetics,2013,43(6):1860-1870. |
APA | Liu, Li,Shao, Ling,Zhen, Xiantong,&Li, Xuelong.(2013).Learning Discriminative Key Poses for Action Recognition.ieee transactions on cybernetics,43(6),1860-1870. |
MLA | Liu, Li,et al."Learning Discriminative Key Poses for Action Recognition".ieee transactions on cybernetics 43.6(2013):1860-1870. |
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