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Fist tracking using Bayesian network
Lu, P; Chen, YF; Zhang, MD; Wang, YS; Tao, J; Picard, RW
AbstractThis paper presents a Bayesian network based multi-cue fusion method for robust and real-time fist tracking. Firstly, a new strategy, which employs the latest work in face recognition, is used to create accurate color model of the fist automatically. Secondly, color cue and motion cue are used to generate the possible position of the fist. Then, the posterior probability of each possible position is evaluated by Bayesian network, which fuses color cue and appearance cue. Finally, the fist position is approximated by the hypothesis that maximizes a posterior. Experimental results show that our algorithm is real-time and robust.
KeywordMulti-cue Fusion Method
WOS HeadingsScience & Technology ; Technology
Indexed BySCI ; ISTP
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS IDWOS:000234342700033
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Document Type期刊论文
AffiliationChinese Acad Sci, Inst Automat, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Lu, P,Chen, YF,Zhang, MD,et al. Fist tracking using Bayesian network[J]. AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION, PROCEEDINGS,2005,3784(0):257-262.
APA Lu, P,Chen, YF,Zhang, MD,Wang, YS,Tao, J,&Picard, RW.(2005).Fist tracking using Bayesian network.AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION, PROCEEDINGS,3784(0),257-262.
MLA Lu, P,et al."Fist tracking using Bayesian network".AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION, PROCEEDINGS 3784.0(2005):257-262.
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