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	P-laplacian regularized sparse coding for human activity recognition
	Liu, Weifeng1; Zha, Zheng-Jun2; Wang, Yanjiang1; Lu, Ke3; Tao, Dacheng4,5
刊名	Ieee transactions on industrial electronics
	2016-08-01
卷号	63期号:8页码:5120-5129
关键词	Human activity recognition Manifold P-laplacian Sparse coding
ISSN号	0278-0046
DOI	10.1109/tie.2016.2552147
通讯作者	Liu, weifeng(liuwf@upc.edu.cn)
英文摘要	Human activity analysis in videos has increasingly attracted attention in computer vision research with the massive number of videos now accessible online. although many recognition algorithms have been reported recently, activity representation is challenging. recently, manifold regularized sparse coding has obtained promising performance in action recognition, because it simultaneously learns the sparse representation and preserves the manifold structure. in this paper, we propose a generalized version of laplacian regularized sparse coding for human activity recognition called p-laplacian regularized sparse coding (plsc). the proposed method exploits p-laplacian regularization to preserve the local geometry. the p-laplacian is a nonlinear generalization of standard graph laplacian and has tighter isoperimetric inequality. as a result, plsc provides superior theoretical evidence than standard laplacian regularized sparse coding with a proper p. we also provide a fast iterative shrinkage-thresholding algorithm for the optimization of plsc. finally, we input the sparse codes learned by the plsc algorithm into support vector machines and conduct extensive experiments on the unstructured social activity attribute dataset and human motion database (hmdb51) for human activity recognition. the experimental results demonstrate that the proposed plsc algorithm outperforms the manifold regularized sparse coding algorithms including the standard laplacian regularized sparse coding algorithm with a proper p.
WOS关键词	IMAGE ANNOTATION ; K-SVD ; REPRESENTATION ; TRACKING ; DICTIONARIES ; OPTIMIZATION ; AUTOMATION ; ALGORITHM ; SPACE ; MODEL
WOS研究方向	Automation & Control Systems ; Engineering ; Instruments & Instrumentation
WOS类目	Automation & Control Systems ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000384641300046
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2375065
专题	中国科学院大学
通讯作者	Liu, Weifeng
作者单位	1.China Univ Petr East China, Coll Informat & Control Engn, Qingdao 266580, Peoples R China 2.Univ Sci & Technol China, Sch Informat Sci & Technol, Hefei 230026, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Univ Technol Sydney, Ctr Quantum Computat & Intelligent Syst, Ultimo, NSW 2007, Australia 5.Univ Technol Sydney, Fac Engn & Informat Technol, Ultimo, NSW 2007, Australia
推荐引用方式 GB/T 7714	Liu, Weifeng,Zha, Zheng-Jun,Wang, Yanjiang,et al. P-laplacian regularized sparse coding for human activity recognition[J]. Ieee transactions on industrial electronics,2016,63(8):5120-5129.
APA	Liu, Weifeng,Zha, Zheng-Jun,Wang, Yanjiang,Lu, Ke,&Tao, Dacheng.(2016).P-laplacian regularized sparse coding for human activity recognition.Ieee transactions on industrial electronics,63(8),5120-5129.
MLA	Liu, Weifeng,et al."P-laplacian regularized sparse coding for human activity recognition".Ieee transactions on industrial electronics 63.8(2016):5120-5129.

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