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Volumn 3953 LNCS, Issue , 2006, Pages 606-618

Effective appearance model and similarity measure for particle filtering and visual tracking

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; DIGITAL ARITHMETIC; FEATURE EXTRACTION; IMAGE ANALYSIS; TRACKING (POSITION);

EID: 33745859744     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11744078_47     Document Type: Conference Paper
Times cited : (33)

References (22)
  • 3
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    • Condensation-conditional density propagation for visual tracking
    • Isard, M. and A. Blake, Condensation-Conditional Density Propagation for Visual Tracking. International Journal of Computer Vision, 1998. 29(1): p. 5-28.
    • (1998) International Journal of Computer Vision , vol.29 , Issue.1 , pp. 5-28
    • Isard, M.1    Blake, A.2
  • 7
    • 13344250690 scopus 로고    scopus 로고
    • Data fusion for visual tracking with particles
    • Perez, P., J. Vermaak, and A. Blake, Data Fusion for Visual Tracking with Particles. Proceedings of the IEEE, 2004. 92(3): p. 495-513.
    • (2004) Proceedings of the IEEE , vol.92 , Issue.3 , pp. 495-513
    • Perez, P.1    Vermaak, J.2    Blake, A.3
  • 9
    • 33744958383 scopus 로고    scopus 로고
    • Integral histogram: A fast way to extract histograms in cartesian spaces
    • Porikli, F. Integral Histogram: A Fast Way to Extract Histograms in Cartesian Spaces. Computer Vision and Pattern Recognition. 2005. p. 829-836.
    • (2005) Computer Vision and Pattern Recognition , pp. 829-836
    • Porikli, F.1
  • 10
    • 7444266896 scopus 로고    scopus 로고
    • Visual tracking and recognition using appearance-adaptive models in particle filters
    • Zhou, S., R. Chellappa, and B. Moghaddam, Visual Tracking and Recognition Using Appearance-Adaptive Models in Particle Filters. IEEE Transactions on Image Processing, 2004, 11: p. 1434-1456.
    • (2004) IEEE Transactions on Image Processing , vol.11 , pp. 1434-1456
    • Zhou, S.1    Chellappa, R.2    Moghaddam, B.3
  • 12
    • 84957655116 scopus 로고    scopus 로고
    • ICONDENSATION: Unifying low-level and high-level tracking in a stochastic framework
    • Isard, M. and A. Blake. ICONDENSATION: Unifying Low-level and High-level Tracking in a Stochastic Framework. European Conference on Computer Vision. 1998. p. 893-908.
    • (1998) European Conference on Computer Vision , pp. 893-908
    • Isard, M.1    Blake, A.2
  • 14
    • 33645307063 scopus 로고    scopus 로고
    • Background and foreground modeling using non-parametric kernel density estimation for visual surveillance
    • Elgammal, A., et al., Background and Foreground Modeling using Non-parametric Kernel Density Estimation for Visual Surveillance. Proceedings of the IEEE, 2002. 90(7): p. 1151-1163.
    • (2002) Proceedings of the IEEE , vol.90 , Issue.7 , pp. 1151-1163
    • Elgammal, A.1
  • 15
    • 24644452614 scopus 로고    scopus 로고
    • Efficient mean-shift tracking via a new similarity measure
    • Yang, C. R. Duraiswami, and L.S. Davis. Efficient Mean-Shift Tracking via a New Similarity Measure. Computer Vision and Pattern Recognition. 2005. p. 176-183.
    • (2005) Computer Vision and Pattern Recognition , pp. 176-183
    • Yang, C.R.D.1    Davis, L.S.2
  • 16
    • 0033098507 scopus 로고    scopus 로고
    • Tracking colour objects using adaptive mixture models
    • McKenna, S.J., Y. Raja, and S. Gong, Tracking Colour Objects Using Adaptive Mixture Models. Image and Vision Computing, 1999.17: p. 225-231.
    • (1999) Image and Vision Computing , vol.17 , pp. 225-231
    • McKenna, S.J.1    Raja, Y.2    Gong, S.3
  • 18
    • 33745827671 scopus 로고    scopus 로고
    • On-line density-based appearance modeling for object tracking
    • Han, B. and L. Davis. On-Line Density-Based Appearance Modeling for Object Tracking. International Conference on Computer Vision. 2005. p. 1492-1499.
    • (2005) International Conference on Computer Vision , pp. 1492-1499
    • Han, B.1    Davis, L.2
  • 19
    • 3543134710 scopus 로고    scopus 로고
    • Robust visual tracking by integrating multiple cues based on co-inference learning
    • Wu, Y. and T.S. Huang, Robust Visual Tracking by Integrating Multiple Cues Based on Co-Inference Learning. International Journal of Computer Vision, 2004. 58(1): p. 55-71.
    • (2004) International Journal of Computer Vision , vol.58 , Issue.1 , pp. 55-71
    • Wu, Y.1    Huang, T.S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.