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Volumn , Issue , 2008, Pages

Fast algorithms for large scale conditional 3D prediction

Author keywords

[No Author keywords available]

Indexed keywords

3-D RECONSTRUCTIONS; APPLICATION DOMAINS; BAYESIAN MIXTURES; BOUND OPTIMIZATION; DATA SETS; DISCRIMINATIVE LEARNING; FAST ALGORITHMS; FEATURE SELECTION; HUMAN POSE; LARGE-SCALE EXPERIMENTS; LOOP ALGORITHMS; MODELING TOOLS; ORDER-OF MAGNITUDES; PREDICTIVE ALGORITHMS; TRAINING SETS;

EID: 51949094782     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2008.4587578     Document Type: Conference Paper
Times cited : (81)

References (25)
  • 1
    • 5044228983 scopus 로고    scopus 로고
    • A. Agarwal and B. Triggs. 3d human pose from silhouettes by Relevance Vector Regression. In CVPR, 2004.
    • A. Agarwal and B. Triggs. 3d human pose from silhouettes by Relevance Vector Regression. In CVPR, 2004.
  • 2
    • 51949104340 scopus 로고    scopus 로고
    • C. Bishop and M. Svensen. Bayesian mixtures of experts. In UAI, 2003.
    • C. Bishop and M. Svensen. Bayesian mixtures of experts. In UAI, 2003.
  • 3
    • 51949104587 scopus 로고    scopus 로고
    • Twin Gaussian Processes for Structured Prediction
    • April
    • L. Bo and C. Sminchisescu. Twin Gaussian Processes for Structured Prediction. Snowbird Learning, April 2008.
    • (2008) Snowbird Learning
    • Bo, L.1    Sminchisescu, C.2
  • 4
    • 0040528764 scopus 로고    scopus 로고
    • Multinomial logistic regression algorithm
    • D. Böhning. Multinomial logistic regression algorithm. Annals of Inst. of Stat. Math., 44:197-200, 2001.
    • (2001) Annals of Inst. of Stat. Math , vol.44 , pp. 197-200
    • Böhning, D.1
  • 5
    • 10444280570 scopus 로고    scopus 로고
    • The TM algorithm for maximising a conditional likelihood function
    • D. Edwards and S. Lauritzen. The TM algorithm for maximising a conditional likelihood function. Biometrika, 88(4):961-972, 2001.
    • (2001) Biometrika , vol.88 , Issue.4 , pp. 961-972
    • Edwards, D.1    Lauritzen, S.2
  • 6
    • 33645307063 scopus 로고    scopus 로고
    • Foreground and background modeling using non-parametric kernel density estimation for visual surveillance
    • A. Elgammal, R. Duraiswami, D. Harwood, and L. Davis. Foreground and background modeling using non-parametric kernel density estimation for visual surveillance. Proc.IEEE, 2002.
    • (2002) Proc.IEEE
    • Elgammal, A.1    Duraiswami, R.2    Harwood, D.3    Davis, L.4
  • 7
    • 0035470889 scopus 로고    scopus 로고
    • Greedy function approximation: A gradient boosting machine
    • J. Friedman. Greedy function approximation: A gradient boosting machine. The Annals of Statistics, 29(5):1189-1232, 2001.
    • (2001) The Annals of Statistics , vol.29 , Issue.5 , pp. 1189-1232
    • Friedman, J.1
  • 8
    • 33745561205 scopus 로고    scopus 로고
    • An Introduction to Variable and Feature Selection
    • I. Guyon. An Introduction to Variable and Feature Selection. JMLR, 3:1157-1182, 2003.
    • (2003) JMLR , vol.3 , pp. 1157-1182
    • Guyon, I.1
  • 9
    • 0012708049 scopus 로고    scopus 로고
    • On reversing Jensen's inequality
    • T. Jebara and A. Pentland. On reversing Jensen's inequality. In NIPS, 2000.
    • (2000) NIPS
    • Jebara, T.1    Pentland, A.2
  • 10
    • 0000262562 scopus 로고
    • Hierarchical mixtures of experts and the EM algorithm
    • M. Jordan and R. Jacobs. Hierarchical mixtures of experts and the EM algorithm. Neural Computation, (6):181-214, 1994.
    • (1994) Neural Computation , vol.6 , pp. 181-214
    • Jordan, M.1    Jacobs, R.2
  • 11
    • 51949093497 scopus 로고    scopus 로고
    • Semi-Supervised Hierarchical Models for 3D Human Pose Reconstruction
    • A. Kanaujia, C. Sminchisescu, and D. Metaxas. Semi-Supervised Hierarchical Models for 3D Human Pose Reconstruction. In CVPR, 2006.
    • (2006) CVPR
    • Kanaujia, A.1    Sminchisescu, C.2    Metaxas, D.3
  • 12
    • 21244437589 scopus 로고    scopus 로고
    • Sparse multinomial logistic regression: Fast algorithms and generalization bounds
    • B. Krishnapuram, L. Carin, M. T. Figueiredo, and A. J. Hartemink. Sparse multinomial logistic regression: Fast algorithms and generalization bounds. PAMI, 27(6):957-968, 2005.
    • (2005) PAMI , vol.27 , Issue.6 , pp. 957-968
    • Krishnapuram, B.1    Carin, L.2    Figueiredo, M.T.3    Hartemink, A.J.4
  • 14
    • 50649114839 scopus 로고    scopus 로고
    • The Joint Manifold Model for Semi-supervised Multi-valued Regression
    • R. Navaratnam, A. Fitzgibbon, and R. Cipolla. The Joint Manifold Model for Semi-supervised Multi-valued Regression. In ICCV, 2007.
    • (2007) ICCV
    • Navaratnam, R.1    Fitzgibbon, A.2    Cipolla, R.3
  • 15
    • 51949085389 scopus 로고    scopus 로고
    • Evaluating example-based human pose estimation: Experiments on HumanEva sets
    • R. Poppe. Evaluating example-based human pose estimation: Experiments on HumanEva sets . In HumanEva Workshop CVPR, 2007.
    • (2007) HumanEva Workshop CVPR
    • Poppe, R.1
  • 16
    • 84898930685 scopus 로고    scopus 로고
    • Learning Body Pose Via Specialized Maps
    • R. Rosales and S. Sclaroff. Learning Body Pose Via Specialized Maps. In NIPS, 2002.
    • (2002) NIPS
    • Rosales, R.1    Sclaroff, S.2
  • 17
    • 33745987673 scopus 로고    scopus 로고
    • Fast forward selection to speed up sparse gaussian process regression
    • M. Seeger, C. Williams, and N. Lawrence. Fast forward selection to speed up sparse gaussian process regression. In AISTATS, 2003.
    • (2003) AISTATS
    • Seeger, M.1    Williams, C.2    Lawrence, N.3
  • 18
    • 0345414554 scopus 로고    scopus 로고
    • Fast Pose Estimation with Parameter Sensitive Hashing
    • G. Shakhnarovich, P. Viola, and T. Darrell. Fast Pose Estimation with Parameter Sensitive Hashing. In ICCV, 2003.
    • (2003) ICCV
    • Shakhnarovich, G.1    Viola, P.2    Darrell, T.3
  • 19
    • 36348977424 scopus 로고    scopus 로고
    • HumanEva: Synchronized Video and Motion Capture Dataset for Evaluation of Articulated Human Motion
    • Technical Report CS-06-08, Brown University
    • L. Sigal and M. Black. HumanEva: Synchronized Video and Motion Capture Dataset for Evaluation of Articulated Human Motion. Technical Report CS-06-08, Brown University, 2006.
    • (2006)
    • Sigal, L.1    Black, M.2
  • 21
    • 24644445659 scopus 로고    scopus 로고
    • Discriminative Density Propagation for 3D Human Motion Estimation
    • C. Sminchisescu, A. Kanaujia, Z. Li, and D. Metaxas. Discriminative Density Propagation for 3D Human Motion Estimation. In CVPR, volume 1, pages 390-397, 2005.
    • (2005) CVPR , vol.1 , pp. 390-397
    • Sminchisescu, C.1    Kanaujia, A.2    Li, Z.3    Metaxas, D.4
  • 22
    • 34548780282 scopus 로고    scopus 로고
    • 3E: Discriminative Density Propagation for Visual Tracking. PAMI, 2007.
    • 3E: Discriminative Density Propagation for Visual Tracking. PAMI, 2007.
  • 23
    • 14344264768 scopus 로고    scopus 로고
    • Fast marginal likelihood maximisation for sparse bayesian models
    • M. Tipping and A. Faul. Fast marginal likelihood maximisation for sparse bayesian models. In AISTATS, 2003.
    • (2003) AISTATS
    • Tipping, M.1    Faul, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.