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Human silhouette extraction based on HMM

dc.citation.epage997en_US
dc.citation.spage994en_US
dc.contributor.authorZhao, San-Lungen_US
dc.contributor.authorLee, Hsi-Jianen_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.date.accessioned2014-12-08T15:25:02Z
dc.date.available2014-12-08T15:25:02Z
dc.date.issued2006en_US
dc.description.abstractThis paper presents a system that can extract regions of a person from an image sequence. The system first detects foreground regions based on a background model. After foreground regions are extracted a human model is used to identify human regions. In the human model, we adopt a Hidden Markov Model (HMM to model human silhouettes. To separate human and non-human regions, we represent non-human silhouettes by another HMM. The human silhouette model can extract incomplete human regions even when parts of the person are covered by background objects. Experimental results show the system proposed is very effective.en_US
dc.identifier.isbn0-7695-2521-0en_US
dc.identifier.issn1051-4651en_US
dc.identifier.journal18th International Conference on Pattern Recognition, Vol 2, Proceedingsen_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/17414
dc.identifier.wosnumberWOS:000240678300241
dc.language.isoen_USen_US
dc.titleHuman silhouette extraction based on HMMen_US
dc.typeProceedings Paperen_US

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