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Volumn 1, Issue , 2006, Pages 666-673

Multi-object tracking through simultaneous long occlusions and split-merge conditions

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATED ANALYSIS; TRACKING FAILURES;

EID: 33845592424     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2006.195     Document Type: Conference Paper
Times cited : (271)

References (10)
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    • J. Black, T. Ellis, and P. Rosin. A novel method for video tracking performance evaluation. In PETS, pages 125-132, 2003.
    • (2003) PETS , pp. 125-132
    • Black, J.1    Ellis, T.2    Rosin, P.3
  • 2
    • 0032131393 scopus 로고    scopus 로고
    • Object identification: A Bayesian analysis with application to traffic surveillance
    • T. Huang and S. Russell. Object identification: A Bayesian analysis with application to traffic surveillance. Artifical In telligence, 103, 1998.
    • (1998) Artifical in Telligence , vol.13
    • Huang, T.1    Russell, S.2
  • 3
    • 33745127415 scopus 로고    scopus 로고
    • A unified framework for tracking through occlusions and across sensor gaps
    • R. Kaucic, A. G. A. Perera, G. Brooksby, J. Kaufhold, and A. Hoogs. A unified framework for tracking through occlusions and across sensor gaps. In Proc. CVPR, pages 990-997, 2005.
    • (2005) Proc. CVPR , pp. 990-997
    • Kaucic, R.1    Perera, A.G.A.2    Brooksby, G.3    Kaufhold, J.4    Hoogs, A.5
  • 4
    • 33745143619 scopus 로고    scopus 로고
    • Multitarget tracking with split and merged measurements
    • IEEE
    • Z. Khan, B. Tucker, and F. Dellaert. Multitarget tracking with split and merged measurements. In Proc. CVPR. IEEE, 2005.
    • (2005) Proc. CVPR
    • Khan, Z.1    Tucker, B.2    Dellaert, F.3
  • 7
    • 0028112849 scopus 로고
    • Good features to track
    • J. Shi and C. Tomasi. Good features to track. In Proc. CVPR, pages 593-600, 1994.
    • (1994) Proc. CVPR , pp. 593-600
    • Shi, J.1    Tomasi, C.2
  • 9
    • 0032634283 scopus 로고    scopus 로고
    • Adaptive background mixture models for real-time tracking
    • C. Stauffer and E. Grimson. Adaptive background mixture models for real-time tracking. In Proc. CVPR, pages 246-252, 1999.
    • (1999) Proc. CVPR , pp. 246-252
    • Stauffer, C.1    Grimson, E.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.