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Volumn 4843 LNCS, Issue PART 1, 2007, Pages 159-168

Non-parametric background and shadow modeling for object detection

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; IMAGE ANALYSIS; IMAGE RECONSTRUCTION; MATHEMATICAL MODELS; PIXELS; PROBABILITY DENSITY FUNCTION;

EID: 38149077423     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-76386-4_14     Document Type: Conference Paper
Times cited : (23)

References (13)
  • 1
    • 13344250629 scopus 로고    scopus 로고
    • Sequential Kernel Density Approximation through Mode Propagation: Applications to Background Modeling
    • Han, B., Comaniciu, D., Davis, L.: Sequential Kernel Density Approximation through Mode Propagation: Applications to Background Modeling. In: Asian Conference on Computer Vision 2004, pp. 818-823 (2004)
    • (2004) Asian Conference on Computer Vision , pp. 818-823
    • Han, B.1    Comaniciu, D.2    Davis, L.3
  • 2
    • 33645307063 scopus 로고    scopus 로고
    • Background and Foreground Modeling Using Nonparametric Kernel Density Estimation for Visual Surveillance
    • Elgammal, A., Duraiswami, R., Harwood, D., Davis, L.S.: Background and Foreground Modeling Using Nonparametric Kernel Density Estimation for Visual Surveillance. In: Proceedings of the IEEE, vol. 90, pp. 1151-1163 (2002)
    • (2002) Proceedings of the IEEE , vol.90 , pp. 1151-1163
    • Elgammal, A.1    Duraiswami, R.2    Harwood, D.3    Davis, L.S.4
  • 4
    • 84950000200 scopus 로고    scopus 로고
    • A Framework for High-Level Feedback to Adaptive, Per-Pixel, Mixture-of-Gaussian Background Models
    • Harville, M.: A Framework for High-Level Feedback to Adaptive, Per-Pixel, Mixture-of-Gaussian Background Models. In: the 7th European Conference on Computer Vision, vol. III, pp. 543-560 (2002)
    • (2002) the 7th European Conference on Computer Vision , vol.3 , pp. 543-560
    • Harville, M.1
  • 5
    • 35048845530 scopus 로고    scopus 로고
    • Lee, D.-S.: Online Adaptive Gaussian Mixture Learning for Video Applications. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, 3021, pp. 105-116. Springer, Heidelberg (2004)
    • Lee, D.-S.: Online Adaptive Gaussian Mixture Learning for Video Applications. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 105-116. Springer, Heidelberg (2004)
  • 8
    • 85143190979 scopus 로고    scopus 로고
    • Salvador, E., Cavallaro, A., Ebrahimi, T.: SHADOW IDENTIFICATION AND CLASSIFICATION USING INVARIANT COLOR MODELS. In: Proc. of IEEE International Conference on Acoustics, 3, pp. 1545-1548 (2001)
    • Salvador, E., Cavallaro, A., Ebrahimi, T.: SHADOW IDENTIFICATION AND CLASSIFICATION USING INVARIANT COLOR MODELS. In: Proc. of IEEE International Conference on Acoustics, vol. 3, pp. 1545-1548 (2001)
  • 13
    • 0001473437 scopus 로고
    • On the estimation of a probability density function and mode
    • Parzen, E.: On the estimation of a probability density function and mode. The Annals of Mathematical Statistics 33(3), 1065-1076 (1962)
    • (1962) The Annals of Mathematical Statistics , vol.33 , Issue.3 , pp. 1065-1076
    • Parzen, E.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.