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Volumn , Issue , 2008, Pages

People tracking with the Laplacian Eigenmaps Latent Variable Model

Author keywords

[No Author keywords available]

Indexed keywords

PRINCIPAL COMPONENT ANALYSIS; PROBABILITY DENSITY FUNCTION;

EID: 85161972396     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (23)

References (17)
  • 1
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    • The laplacian eigenmaps latent variable model
    • M. Á. Carreira-Perpiñán and Z. Lu. The Laplacian Eigenmaps Latent Variable Model. In AISTATS, 2007.
    • (2007) AISTATS
    • Carreira-Perpiñán, M.A.1    Lu, Z.2
  • 2
    • 0003940328 scopus 로고    scopus 로고
    • Bayesian reconstruction of 3D human motion from single-camera video
    • N. R. Howe, M. E. Leventon, and W. T. Freeman. Bayesian reconstruction of 3D human motion from single-camera video. In NIPS, volume 12, pages 820-826, 2000.
    • (2000) NIPS , vol.12 , pp. 820-826
    • Howe, N.R.1    Leventon, M.E.2    Freeman, W.T.3
  • 3
    • 0032627094 scopus 로고    scopus 로고
    • A multiple hypothesis approach to figure tracking
    • T.-J. Cham and J. M. Rehg. A multiple hypothesis approach to figure tracking. In CVPR, 1999.
    • (1999) CVPR
    • Cham, T.-J.1    Rehg, J.M.2
  • 5
    • 0042420029 scopus 로고    scopus 로고
    • Implicit probabilistic models of human motion for synthesis and tracking
    • H. Sidenbladh, M. J. Black, and L. Sigal. Implicit probabilistic models of human motion for synthesis and tracking. In ECCV, volume 1, pages 784-800, 2002.
    • (2002) ECCV , vol.1 , pp. 784-800
    • Sidenbladh, H.1    Black, M.J.2    Sigal, L.3
  • 9
    • 33845564230 scopus 로고    scopus 로고
    • Gaussian process dynamical models
    • J.M.Wang, D. Fleet, and A. Hertzmann. Gaussian process dynamical models. In NIPS, volume 18, 2006.
    • (2006) NIPS , vol.18
    • Wang, J.M.1    Fleet, D.2    Hertzmann, A.3
  • 11
    • 84864026688 scopus 로고    scopus 로고
    • Modeling human motion using binary latent variables
    • G. W. Taylor, G. E. Hinton, and S. Roweis. Modeling human motion using binary latent variables. In NIPS, volume 19, 2007.
    • (2007) NIPS , vol.19
    • Taylor, G.W.1    Hinton, G.E.2    Roweis, S.3
  • 12
    • 0347963789 scopus 로고    scopus 로고
    • GTM: The generative topographic mapping
    • C. M. Bishop, M. Svensén, and C. K. I. Williams. GTM: The generative topographic mapping. Neural Computation, 10(1):215-234, January 1998. (Pubitemid 128463659)
    • (1998) Neural Computation , vol.10 , Issue.1 , pp. 215-234
    • Bishop, C.M.1    Svensen, M.2    Williams, C.K.I.3
  • 13
    • 27844605876 scopus 로고    scopus 로고
    • Probabilistic non-linear principal component analysis with Gaussian process latent variable models
    • November
    • N. Lawrence. Probabilistic non-linear principal component analysis with Gaussian process latent variable models. Journal of Machine Learning Research, 6:1783-1816, November 2005.
    • (2005) Journal of Machine Learning Research , vol.6 , pp. 1783-1816
    • Lawrence, N.1
  • 14
    • 0042378381 scopus 로고    scopus 로고
    • Laplacian eigenmaps for dimensionality reduction and data representation
    • DOI 10.1162/089976603321780317
    • M. Belkin and P. Niyogi. Laplacian eigenmaps for dimensionality reduction and data representation. Neural Computation, 15(6):1373-1396, June 2003. (Pubitemid 37049796)
    • (2003) Neural Computation , vol.15 , Issue.6 , pp. 1373-1396
    • Belkin, M.1    Niyogi, P.2
  • 16
    • 0141630418 scopus 로고    scopus 로고
    • Gaussian mixture sigma-point particle filters for sequential probabilistic inference in dynamic state-space models
    • R. van derMerwe and E. A.Wan. Gaussian mixture sigma-point particle filters for sequential probabilistic inference in dynamic state-space models. In ICASSP, volume 6, pages 701-704, 2003.
    • (2003) ICASSP , vol.6 , pp. 701-704
    • Van Der Merwe, R.1    Wan, E.A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.