메뉴 건너뛰기




Volumn 18, Issue 9, 2008, Pages 1268-1279

Dynamic proposal variance and optimal particle allocation in particle filtering for video tracking

Author keywords

Dynamic proposal variance; Optimal particle allocation; Particle filter; Tracking distortion; Video tracking

Indexed keywords

ACOUSTIC SIGNAL PROCESSING; BOOLEAN FUNCTIONS; ERROR ANALYSIS; NONLINEAR FILTERING; PHOTOGRAPHY; TELEVISION EQUIPMENT; VIDEO RECORDING;

EID: 53849127873     PISSN: 10518215     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCSVT.2008.928889     Document Type: Article
Times cited : (43)

References (25)
  • 1
    • 0032136153 scopus 로고    scopus 로고
    • Condensation - conditional density propagation for visual tracking
    • M. Isard and A. Blake, "Condensation - conditional density propagation for visual tracking," Int. J. Comput. Vis., vol. 29, no. 1, pp. 5-28, 1998.
    • (1998) Int. J. Comput. Vis , vol.29 , Issue.1 , pp. 5-28
    • Isard, M.1    Blake, A.2
  • 2
    • 21844442647 scopus 로고    scopus 로고
    • Complete system for head tracking using motion-based particle filter and randomly perturbed active contour
    • N. Bouaynaya and D. Schonfeld, "Complete system for head tracking using motion-based particle filter and randomly perturbed active contour," Proc .SPIE, vol. 5685, pp. 864-873, 2005.
    • (2005) Proc .SPIE , vol.5685 , pp. 864-873
    • Bouaynaya, N.1    Schonfeld, D.2
  • 3
    • 33646778505 scopus 로고    scopus 로고
    • Automatic multi-head detection and tracking system using a novel detection-based particle filter and data fusion
    • W. Qu, N. Bouaynaya, and D. Schonfeld, "Automatic multi-head detection and tracking system using a novel detection-based particle filter and data fusion," in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., 2005, vol. 2, pp. 661-664.
    • (2005) Proc. IEEE Int. Conf. Acoust., Speech, Signal Process , vol.2 , pp. 661-664
    • Qu, W.1    Bouaynaya, N.2    Schonfeld, D.3
  • 4
    • 13344250690 scopus 로고    scopus 로고
    • Data fusion for visual tracking with, particles
    • Mar
    • P. Prez, J. Vermaak, and A. Blake, "Data fusion for visual tracking with, particles," Proc. IEEE, vol. 92, no. 3, pp. 495-513, Mar. 2004.
    • (2004) Proc. IEEE , vol.92 , Issue.3 , pp. 495-513
    • Prez, P.1    Vermaak, J.2    Blake, A.3
  • 5
    • 0003838908 scopus 로고    scopus 로고
    • On Sequential Simulation-Based Methods for Bayesian. Filtering Signal Processing Group, Dept. Eng., Univ. of Cambridge, Cambridge
    • 3.10
    • A. Doucet, On Sequential Simulation-Based Methods for Bayesian. Filtering Signal Processing Group, Dept. Eng., Univ. of Cambridge, Cambridge, 1998, Tech. Rep. CUED/F-INFENG/TR. 3.10.
    • (1998) Tech. Rep. CUED/F-INFENG/TR
    • Doucet, A.1
  • 6
    • 33947575392 scopus 로고    scopus 로고
    • Real-time distributed multiobject tracking using multiple interactive trackers and a magnetic-inertia potential model
    • Apr
    • W. Qu, D. Schonfeld, and M. Mohamed, "Real-time distributed multiobject tracking using multiple interactive trackers and a magnetic-inertia potential model," IEEE Trans. Multimedia, vol. 9, no. 3, pp. 511-519, Apr. 2007.
    • (2007) IEEE Trans. Multimedia , vol.9 , Issue.3 , pp. 511-519
    • Qu, W.1    Schonfeld, D.2    Mohamed, M.3
  • 7
    • 0036475204 scopus 로고    scopus 로고
    • A bayesian approach to tracking multiple targets using sensor arrays and particle filters
    • Feb
    • M. Orton and W. Fitzgerald, "A bayesian approach to tracking multiple targets using sensor arrays and particle filters," IEEE Trans. Signal Process., vol. 50, no. 2, pp. 216-223, Feb. 2002.
    • (2002) IEEE Trans. Signal Process , vol.50 , Issue.2 , pp. 216-223
    • Orton, M.1    Fitzgerald, W.2
  • 11
    • 0036475447 scopus 로고    scopus 로고
    • A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking
    • Feb
    • M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, "A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking," IEEE Trans. Signal Process., vol. 50, no. 2, pp. 174-188, Feb. 2002.
    • (2002) IEEE Trans. Signal Process , vol.50 , Issue.2 , pp. 174-188
    • Arulampalam, M.S.1    Maskell, S.2    Gordon, N.3    Clapp, T.4
  • 12
    • 0003987291 scopus 로고    scopus 로고
    • Using learning for approximation in stochastic processes
    • D. Koller and R. Fratkina, "Using learning for approximation in stochastic processes," in Proc. Int. Conf. Mach. Learning, 1998, pp. 287-295.
    • (1998) Proc. Int. Conf. Mach. Learning , pp. 287-295
    • Koller, D.1    Fratkina, R.2
  • 13
    • 0344445520 scopus 로고    scopus 로고
    • Adapting the sample size in particle filters through kidsampling
    • D. Fox, "Adapting the sample size in particle filters through kidsampling," Int. J. Robot. Res., vol. 22, no. 12, pp. 985-1003, 2003.
    • (2003) Int. J. Robot. Res , vol.22 , Issue.12 , pp. 985-1003
    • Fox, D.1
  • 15
    • 0035691549 scopus 로고    scopus 로고
    • Better proposal distributions: Object tracking using unscented particle filter
    • Y. Rui and Y. Chen, "Better proposal distributions: Object tracking using unscented particle filter," in Proc. IEEE Conf. Comput. Vis. Pattern Recogn., 2001, pp. 786-793.
    • (2001) Proc. IEEE Conf. Comput. Vis. Pattern Recogn , pp. 786-793
    • Rui, Y.1    Chen, Y.2
  • 16
    • 0008782869 scopus 로고    scopus 로고
    • Improvement strategies for Monte Carlo particle filters
    • New York: Springer-Verlag
    • S. J. Godsill and T. C. Clapp, "Improvement strategies for Monte Carlo particle filters," in Sequential Monte Carlo Methods in Practice. New York: Springer-Verlag, 2001.
    • (2001) Sequential Monte Carlo Methods in Practice
    • Godsill, S.J.1    Clapp, T.C.2
  • 17
    • 84957655116 scopus 로고    scopus 로고
    • Icondensation: Unifying low-level and high-level tracking in a stochastic framework
    • M. Isard and A. Blake, "Icondensation: Unifying low-level and high-level tracking in a stochastic framework," in Proc. Eur: Conf. Comput. Vis., 1998, pp. 893-908.
    • (1998) Proc. Eur: Conf. Comput. Vis , pp. 893-908
    • Isard, M.1    Blake, A.2
  • 19
    • 84944037559 scopus 로고    scopus 로고
    • Partitioned sampling, articulated objects, and interface-quality hand tracking
    • J. MacCormick and M. Isard, "Partitioned sampling, articulated objects, and interface-quality hand tracking," in Proc. Eur. Conf. Comput. Vis., 2000, pp. 3-19.
    • (2000) Proc. Eur. Conf. Comput. Vis , pp. 3-19
    • MacCormick, J.1    Isard, M.2
  • 21
    • 0036504051 scopus 로고    scopus 로고
    • A survey of convergence results on particle filtering methods for practitioners
    • Mar
    • D. Crisan and A. Doucet, "A survey of convergence results on particle filtering methods for practitioners," IEEE Trans. Signal Process., vol. 50, no. 3, pp. 736-746, Mar. 2002.
    • (2002) IEEE Trans. Signal Process , vol.50 , Issue.3 , pp. 736-746
    • Crisan, D.1    Doucet, A.2
  • 23
    • 26844431934 scopus 로고    scopus 로고
    • Fast object tracking using adaptive block matching
    • Oct
    • K. Hariharakrishnan and D. Schonfeld, "Fast object tracking using adaptive block matching," IEEE Trans. Multimedia, vol. 7, no. 5, pp. 853-859, Oct. 2005.
    • (2005) IEEE Trans. Multimedia , vol.7 , Issue.5 , pp. 853-859
    • Hariharakrishnan, K.1    Schonfeld, D.2
  • 24
    • 0036994158 scopus 로고    scopus 로고
    • Adaptive rood pattern search for fast block-matching motion estimation
    • Dec
    • Y. Nie and K.-K. Ma, "Adaptive rood pattern search for fast block-matching motion estimation," IEEE Trans. Image Process., vol. 11, no. 12, pp. 1442-1449, Dec. 2002.
    • (2002) IEEE Trans. Image Process , vol.11 , Issue.12 , pp. 1442-1449
    • Nie, Y.1    Ma, K.-K.2
  • 25
    • 84878582609 scopus 로고    scopus 로고
    • Object tracking with an adaptive color-based particle filter
    • K. Nummiaro, E. Koller-Meier, and L. V. Gool, "Object tracking with an adaptive color-based particle filter," in Proc. DAGM Symp. Recogn., 2002, pp. 353-360.
    • (2002) Proc. DAGM Symp. Recogn , pp. 353-360
    • Nummiaro, K.1    Koller-Meier, E.2    Gool, L.V.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.