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Volumn , Issue , 2008, Pages

Efficient background modeling through incremental Support Vector Data Description

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); PATTERN RECOGNITION; VIDEO SIGNAL PROCESSING;

EID: 77957969681     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/icpr.2008.4761328     Document Type: Conference Paper
Times cited : (12)

References (8)
  • 1
    • 0003120218 scopus 로고    scopus 로고
    • Fast training of support vector machines using sequential minimal optimization
    • MIT Press
    • J. Platt. Fast Training of Support Vector Machines using Sequential Minimal Optimization. Advances in Kernel Methods - Support Vector Learning., MIT Press:185- 208., 1998.
    • (1998) Advances in Kernel Methods - Support Vector Learning , pp. 185-208
    • Platt, J.1
  • 2
    • 7444243389 scopus 로고    scopus 로고
    • Statistical modeling of complex backgrounds for foreground object detection
    • November
    • L. Li, W. Huang, I. Gu, and Q. Tian. Statistical modeling of complex backgrounds for foreground object detection. IEEE Transactions on Image Processing., 13(11):1459- 1472, November 2004.
    • (2004) IEEE Transactions on Image Processing , vol.13 , Issue.11 , pp. 1459-1472
    • Li, L.1    Huang, W.2    Gu, I.3    Tian, Q.4
  • 4
    • 0034244889 scopus 로고    scopus 로고
    • Learning patterns of activity using real-time tracking
    • August
    • C. Stauffer and W. Grimson. Learning Patterns of Activity using Real-Time Tracking. IEEE Transactions on PAMI, 22(8):747-757, August 2000.
    • (2000) IEEE Transactions on PAMI , vol.22 , Issue.8 , pp. 747-757
    • Stauffer, C.1    Grimson, W.2
  • 6
    • 0942266514 scopus 로고    scopus 로고
    • Support vector data description
    • D. Tax and R. Duin. Support Vector Data Description. Machine Learning, 54(1):45-66., 2004.
    • (2004) Machine Learning , vol.54 , Issue.1 , pp. 45-66
    • Tax, D.1    Duin, R.2
  • 7
    • 79960753941 scopus 로고    scopus 로고
    • Online SVM learning: From classification and data description and back
    • D. Tax and P. Laskov. Online SVM Learning: from Classification and Data Description and Back. Neural Networks and Signal Processing, (1):499-508., 2003.
    • (2003) Neural Networks and Signal Processing , Issue.1 , pp. 499-508
    • Tax, D.1    Laskov, P.2
  • 8
    • 0033285765 scopus 로고    scopus 로고
    • Wallflower: Principles and practice of background maintenance
    • September
    • K. Toyama, J. Krumm, B. Brumitt, and B. Meyers. Wallflower: principles and practice of background maintenance. In proceedings of ICCV, 1:255-261, September 1999.
    • (1999) Proceedings of ICCV , vol.1 , pp. 255-261
    • Toyama, K.1    Krumm, J.2    Brumitt, B.3    Meyers, B.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.