A discriminative representation for human action recognition

doi:10.1016/j.patcog.2016.02.022

OPT OpenIR > 光谱成像技术研究室

	A discriminative representation for human action recognition
	Yuan, Yuan1 ; Zheng, Xiangtao1,2 ; Lu, Xiaoqiang1 ; Lu, Xiaoqiang (luxiaoqiang@opt.ac.cn)
作者部门	光学影像学习与分析中心
	2016-11-01
发表期刊	PATTERN RECOGNITION
ISSN	0031-3203
卷号	59 页码:88-97
产权排序	1
摘要	Action recognition has been standing as an active research topic over the past years. Many efforts have been made and many methods have been proposed. However, there are still some challenges such as illumination condition, viewpoint, camera motion and cluttered background. In order to tackle these challenges, a discriminative representation is proposed by discovering key information of the input data. This task can be addressed by improvements of two major components: parameterized representation and discriminative classifier. The representation is parameterized with hidden variables and can be learned from training data. And the classifier can be trained to recognize actions based on the proposed representation. The contributions of this paper are as follows: (1) a novel probabilistic representation is utilized to capture the relative significant information of low level features; (2) a novel framework is proposed by combining the parameterized representation and discriminative classifier; (3) an alternating strategy is favorable to improve the performance of action recognition by updating the representation and the classifier alternatively. Experimental results on five well-known datasets demonstrate that the proposed method significantly improves the performance in action recognition. (C) 2016 Elsevier Ltd. All rights reserved.
文章类型	Article
关键词	Action Recognition Discriminative Representation Classifier Maximum Likelihood
WOS标题词	Science & Technology ; Technology
DOI	10.1016/j.patcog.2016.02.022
收录类别	SCI ; EI
关键词[WOS]	CLASSIFICATION ; SCENE ; SVM
语种	英语
WOS研究方向	Computer Science ; Engineering
项目资助者	National Basic Research Program of China (973 Program)(2012CB719905) ; State Key Program of National Natural Science of China(61232010) ; National Natural Science Foundation of China(61472413) ; Open Research Fund of Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences(LSIT201408)
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000383007800009
引用统计	被引频次：16[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.opt.ac.cn/handle/181661/28255
专题	光谱成像技术研究室
通讯作者	Lu, Xiaoqiang (luxiaoqiang@opt.ac.cn)
作者单位	1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr OPT IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian 710119, Shaanxi, Peoples R China 2.Univ Chinese Acad Sci, 19A Yuquanlu, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Yuan, Yuan,Zheng, Xiangtao,Lu, Xiaoqiang,et al. A discriminative representation for human action recognition[J]. PATTERN RECOGNITION,2016,59:88-97.
APA	Yuan, Yuan,Zheng, Xiangtao,Lu, Xiaoqiang,&Lu, Xiaoqiang .(2016).A discriminative representation for human action recognition.PATTERN RECOGNITION,59,88-97.
MLA	Yuan, Yuan,et al."A discriminative representation for human action recognition".PATTERN RECOGNITION 59(2016):88-97.

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A discriminative rep（958KB）	期刊论文	作者接受稿	限制开放	CC BY-NC-SA	请求全文