CASIA OpenIR  > 模式识别国家重点实验室  > 多媒体计算与图形学
A Coupled Hidden Markov Random Field model for simultaneous face clustering and tracking in videos
Wu, Baoyuan1,2; Hu, Bao-Gang1; Ji, Qiang3
Source PublicationPATTERN RECOGNITION
2017-04-01
Volume64Issue:2Pages:361-373
SubtypeArticle
AbstractFace clustering and face tracking are two areas of active research in automatic facial video processing. They, however, have long been studied separately, despite the inherent link between them. In this paper, we propose to perform simultaneous face clustering and face tracking from real world videos. The motivation for the proposed research is that face clustering and face tracking can provide useful information and constraints to each other, thus can bootstrap and improve the performances of each other. To this end, we introduce a Coupled Hidden Markov Random Field (CHMRF) to simultaneously model face clustering, face tracking, and their interactions. We provide an effective algorithm based on constrained clustering and optimal tracking for the joint optimization of cluster labels and face tracking. We demonstrate significant improvements over state-ofthe-art results in face clustering and tracking on several videos.
KeywordFace Clustering Face Tracking Coupled Hidden Markov Random Field
WOS HeadingsScience & Technology ; Technology
DOI10.1016/j.patcog.2016.10.022
Indexed BySCI
Language英语
Funding OrganizationChina Scholarship Council (CSC) ; CSC ; RPI ; US National Science Foundation (NSF)(1145152) ; National Natural Science Foundation of China (NSFC)(61273196 ; 61573348)
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000392682400029
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14363
Collection模式识别国家重点实验室_多媒体计算与图形学
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.King Abdullah Univ Sci & Technol, Visual Comp Ctr, Thuwal 239556900, Saudi Arabia
3.Rensselaer Polytech Inst, Dept Elect Comp & Syst Engn, Troy, NY 12180 USA
Recommended Citation
GB/T 7714
Wu, Baoyuan,Hu, Bao-Gang,Ji, Qiang. A Coupled Hidden Markov Random Field model for simultaneous face clustering and tracking in videos[J]. PATTERN RECOGNITION,2017,64(2):361-373.
APA Wu, Baoyuan,Hu, Bao-Gang,&Ji, Qiang.(2017).A Coupled Hidden Markov Random Field model for simultaneous face clustering and tracking in videos.PATTERN RECOGNITION,64(2),361-373.
MLA Wu, Baoyuan,et al."A Coupled Hidden Markov Random Field model for simultaneous face clustering and tracking in videos".PATTERN RECOGNITION 64.2(2017):361-373.
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