Recognizing Gaits Across Views Through Correlated Motion Co-Clustering

CASIA OpenIR > 智能感知与计算研究中心

	Recognizing Gaits Across Views Through Correlated Motion Co-Clustering
	Kusakunniran, Worapan 1; Wu, Qiang 2; Zhang, Jian 3,4; Li, Hongdong 5,6; Wang, Liang7
发表期刊	IEEE TRANSACTIONS ON IMAGE PROCESSING
	2014-02-01
卷号	23 期号:2 页码:696-709
文章类型	Article
摘要	Human gait is an important biometric feature, which can be used to identify a person remotely. However, view change can cause significant difficulties for gait recognition because it will alter available visual features for matching substantially. Moreover, it is observed that different parts of gait will be affected differently by view change. By exploring relations between two gaits from two different views, it is also observed that a part of gait in one view is more related to a typical part than any other parts of gait in another view. A new method proposed in this paper considers such variance of correlations between gaits across views that is not explicitly analyzed in the other existing methods. In our method, a novel motion co-clustering is carried out to partition the most related parts of gaits from different views into the same group. In this way, relationships between gaits from different views will be more precisely described based on multiple groups of the motion co-clustering instead of a single correlation descriptor. Inside each group, a linear correlation between gait information across views is further maximized through canonical correlation analysis (CCA). Consequently, gait information in one view can be projected onto another view through a linear approximation under the trained CCA subspaces. In the end, a similarity between gaits originally recorded from different views can be measured under the approximately same view. Comprehensive experiments based on widely adopted gait databases have shown that our method outperforms the state-of-the-art.
关键词	Gait Recognition Human Identification View Change Co-clustering Bipartite Graph Multipartitioning Canonical Correlation Analysis
WOS标题词	Science & Technology ; Technology
关键词[WOS]	FEATURE-EXTRACTION ; ENERGY IMAGE ; RECOGNITION ; PARAMETERS ; FUSION ; MODEL
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000329581800017
引用统计	被引频次：92[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/8036
专题	智能感知与计算研究中心
作者单位	1.Mahidol Univ, Fac Informat & Commun Technol, Nakhon Pathom 73170, Thailand 2.Univ Technol Sydney, Sch Comp & Commun, Sydney, NSW 2007, Australia 3.Univ Technol Sydney, Fac Engn & Informat Technol, Sch Software, Adv Analyt Inst, Sydney, NSW 2007, Australia 4.Natl ICT Australia, Neville Roach Lab, Kensington, NSW 2052, Australia 5.Australian Natl Univ, Res Sch Informat Sci & Engn, Canberra, ACT 0200, Australia 6.Natl ICT Australia, Canberra Res Lab, Canberra, ACT 2601, Australia 7.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Kusakunniran, Worapan,Wu, Qiang,Zhang, Jian,et al. Recognizing Gaits Across Views Through Correlated Motion Co-Clustering[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2014,23(2):696-709.
APA	Kusakunniran, Worapan,Wu, Qiang,Zhang, Jian,Li, Hongdong,&Wang, Liang.(2014).Recognizing Gaits Across Views Through Correlated Motion Co-Clustering.IEEE TRANSACTIONS ON IMAGE PROCESSING,23(2),696-709.
MLA	Kusakunniran, Worapan,et al."Recognizing Gaits Across Views Through Correlated Motion Co-Clustering".IEEE TRANSACTIONS ON IMAGE PROCESSING 23.2(2014):696-709.