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Volumn , Issue , 2009, Pages 3189-3192

A global probabilistic framework for the foreground, background and shadow classification task

Author keywords

Belief propagation; Foreground segmentation; Global; Markov random fields; Shadow removal

Indexed keywords

IMAGE SEGMENTATION; IMAGING SYSTEMS; MATHEMATICAL MORPHOLOGY; MAXIMUM LIKELIHOOD ESTIMATION; STOCHASTIC MODELS;

EID: 77951947644     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2009.5414388     Document Type: Conference Paper
Times cited : (4)

References (13)
  • 12
    • 33645307063 scopus 로고    scopus 로고
    • Background and foreground modeling using nonparametric kernel density for visual surveillance
    • Ahmed Elgammal, Ramani Duraiswami, David Harwood, and Larry S. Davis, "Background and foreground modeling using nonparametric kernel density for visual surveillance," in Proceedings of the IEEE, July 2002, vol. 90, pp. 1151-1163.
    • Proceedings of the IEEE, July 2002 , vol.90 , pp. 1151-1163
    • Elgammal, A.1    Duraiswami, R.2    Harwood, D.3    Davis, L.S.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.