메뉴 건너뛰기




Volumn , Issue , 2013, Pages 3728-3735

Tracking human pose by tracking symmetric parts

Author keywords

human pose estimation; multi target tracking; mutual exclusion constraints; occlusion reasoning; symmetric parts

Indexed keywords

HUMAN POSE ESTIMATIONS; MULTI-TARGET TRACKING; MUTUAL EXCLUSIONS; OCCLUSION REASONING; SYMMETRIC PARTS;

EID: 84887357826     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2013.478     Document Type: Conference Paper
Times cited : (44)

References (37)
  • 2
    • 24644450309 scopus 로고    scopus 로고
    • Tracking articulated motion using a mixture of autoregressive models
    • 2
    • A. Agarwal and B. Triggs. Tracking articulated motion using a mixture of autoregressive models. ECCV, 2004. 2
    • (2004) ECCV
    • Agarwal, A.1    Triggs, B.2
  • 3
    • 70450203723 scopus 로고    scopus 로고
    • Pictorial structures revisited: People detection and articulated pose estimation
    • 2
    • M. Andriluka, S. Roth, and B. Schiele. Pictorial Structures Revisited: People Detection and Articulated Pose Estimation. CVPR, 2009. 2
    • (2009) CVPR
    • Andriluka, M.1    Roth, S.2    Schiele, B.3
  • 4
    • 77955992058 scopus 로고    scopus 로고
    • Monocular 3d pose estimation and tracking by detection
    • 2
    • M. Andriluka, S. Roth, and B. Schiele. Monocular 3d pose estimation and tracking by detection. CVPR, 2010. 2
    • (2010) CVPR
    • Andriluka, M.1    Roth, S.2    Schiele, B.3
  • 5
    • 80052913607 scopus 로고    scopus 로고
    • Globally optimal multi-target tracking on a hexagonal lattice
    • 2, 4, 5
    • A. Andriyenko and K. Schindler. Globally optimal multi-target tracking on a hexagonal lattice. ECCV, 2010. 2, 4, 5
    • (2010) ECCV
    • Andriyenko, A.1    Schindler, K.2
  • 6
    • 1542285823 scopus 로고    scopus 로고
    • Lucas-kanade 20 years on: A unifying framework
    • 5
    • S. Baker and I. Matthews. Lucas-kanade 20 years on: A unifying framework. IJCV, 2004. 5
    • (2004) IJCV
    • Baker, S.1    Matthews, I.2
  • 7
    • 80054897941 scopus 로고    scopus 로고
    • Multiple object tracking using k-shortest paths optimization
    • 2, 4
    • J. Berclaz, F. Fleuret, E. Turetken, and P. Fua. Multiple object tracking using k-shortest paths optimization. PAMI, 2011. 2, 4
    • (2011) PAMI
    • Berclaz, J.1    Fleuret, F.2    Turetken, E.3    Fua, P.4
  • 8
    • 51949088307 scopus 로고    scopus 로고
    • Progressive search space reduction for human pose estimation
    • 6
    • V. Ferrari, M. Marin-Jimenez, and A. Zisserman. Progressive search space reduction for human pose estimation. In CVPR, 2008. 6
    • (2008) CVPR
    • Ferrari, V.1    Marin-Jimenez, M.2    Zisserman, A.3
  • 11
    • 0014302589 scopus 로고
    • What gives rise to the perception of motion
    • 1
    • J. Gibson. What gives rise to the perception of motion? Psychological Review, 1968. 1
    • (1968) Psychological Review
    • Gibson, J.1
  • 13
    • 84863610103 scopus 로고    scopus 로고
    • Human pose estimation using consistent max-covering
    • 2
    • H. Jiang. Human pose estimation using consistent max-covering. In ICCV, 2009. 2
    • (2009) ICCV
    • Jiang, H.1
  • 14
    • 34948910165 scopus 로고    scopus 로고
    • A linear programming approach for multiple object tracking
    • 2, 4
    • H. Jiang, S. Fels, and J. Little. A linear programming approach for multiple object tracking. In CVPR, 2007. 2, 4
    • (2007) CVPR
    • Jiang, H.1    Fels, S.2    Little, J.3
  • 15
    • 51949102800 scopus 로고    scopus 로고
    • Global pose estimation using non-tree models
    • 2
    • H. Jiang and D. Martin. Global pose estimation using non-tree models. CVPR, 2008. 2
    • (2008) CVPR
    • Jiang, H.1    Martin, D.2
  • 16
    • 84898472539 scopus 로고    scopus 로고
    • Clustered pose and nonlinear appearance models for human pose estimation
    • 2
    • S. Johnson and M. Everingham. Clustered pose and nonlinear appearance models for human pose estimation. In BMVC, 2010. 2
    • (2010) BMVC
    • Johnson, S.1    Everingham, M.2
  • 17
    • 84887380431 scopus 로고    scopus 로고
    • Using linking features in learning nonparametric part models
    • 2
    • L. Karlinsky and S. Ullman. Using linking features in learning nonparametric part models. ECCV, 2012. 2
    • (2012) ECCV
    • Karlinsky, L.1    Ullman, S.2
  • 18
    • 5044224520 scopus 로고    scopus 로고
    • A unified spatio-temporal articulated model for tracking
    • 2
    • X. Lan and D. Huttenlocher. A unified spatio-temporal articulated model for tracking. In CVPR, 2004. 2
    • (2004) CVPR
    • Lan, X.1    Huttenlocher, D.2
  • 19
    • 33745939723 scopus 로고    scopus 로고
    • Beyond trees: Common-factor models for 2d human pose recovery
    • 2
    • X. Lan and D. Huttenlocher. Beyond trees: Common-factor models for 2d human pose recovery. In ICCV, 2005. 2
    • (2005) ICCV
    • Lan, X.1    Huttenlocher, D.2
  • 21
    • 80052884816 scopus 로고    scopus 로고
    • Tracking people's hands and feet using mixed network and/or search
    • 2
    • V. Morariu, D. Harwood, and L. Davis. Tracking people's hands and feet using mixed network and/or search. PAMI, 2012. 2
    • (2012) PAMI
    • Morariu, V.1    Harwood, D.2    Davis, L.3
  • 22
    • 0032292397 scopus 로고    scopus 로고
    • Singularity analysis for articulated object tracking
    • 2
    • D. Morris and J. Rehg. Singularity analysis for articulated object tracking. In CVPR, 1998. 2
    • (1998) CVPR
    • Morris, D.1    Rehg, J.2
  • 23
    • 84856682999 scopus 로고    scopus 로고
    • N-best maximal decoders for part models
    • 2, 6, 7, 8
    • D. Park and D. Ramanan. N-best maximal decoders for part models. In ICCV, 2011. 2, 6, 7, 8
    • (2011) ICCV
    • Park, D.1    Ramanan, D.2
  • 24
    • 84863047620 scopus 로고    scopus 로고
    • 3d reconstruction of a smooth articulated trajectory from a monocular image sequence
    • 1
    • H. Park and Y. Sheikh. 3d reconstruction of a smooth articulated trajectory from a monocular image sequence. ICCV, 2011. 1
    • (2011) ICCV
    • Park, H.1    Sheikh, Y.2
  • 25
    • 84864046033 scopus 로고    scopus 로고
    • Learning to parse images of articulated bodies
    • 2
    • D. Ramanan. Learning to parse images of articulated bodies. NIPS, 2007. 2
    • (2007) NIPS
    • Ramanan, D.1
  • 26
    • 24644504137 scopus 로고    scopus 로고
    • Strike a pose: Tracking people by finding stylized poses
    • 2
    • D. Ramanan, D. Forsyth, and A. Zisserman. Strike a pose: Tracking people by finding stylized poses. In CVPR, 2005. 2
    • (2005) CVPR
    • Ramanan, D.1    Forsyth, D.2    Zisserman, A.3
  • 27
    • 33947211728 scopus 로고    scopus 로고
    • Tracking people by learning their appearance
    • 6
    • D. Ramanan, D. Forsyth, and A. Zisserman. Tracking people by learning their appearance. PAMI, 2007. 6
    • (2007) PAMI
    • Ramanan, D.1    Forsyth, D.2    Zisserman, A.3
  • 29
    • 0027928914 scopus 로고
    • Towards model-based recognition of human movements in image sequences
    • 2
    • K. Rohr. Towards model-based recognition of human movements in image sequences. CVGIP-Image Understanding, 1994. 2
    • (1994) CVGIP-Image Understanding
    • Rohr, K.1
  • 30
    • 80052890828 scopus 로고    scopus 로고
    • Parsing human motion with stretchable models
    • 2
    • B. Sapp, D. Weiss, and B. Taskar. Parsing human motion with stretchable models. In CVPR, 2011. 2
    • (2011) CVPR
    • Sapp, B.1    Weiss, D.2    Taskar, B.3
  • 31
    • 33845575116 scopus 로고    scopus 로고
    • Measure locally, reason globally: Occlusionsensitive articulated pose estimation
    • 1, 2
    • L. Sigal and M. Black. Measure locally, reason globally: Occlusionsensitive articulated pose estimation. In CVPR, 2006. 1, 2
    • (2006) CVPR
    • Sigal, L.1    Black, M.2
  • 32
    • 34548780282 scopus 로고    scopus 로고
    • Bm3e: Discriminative density propagation for visual tracking
    • 2
    • C. Sminchisescu, A. Kanaujia, and D. Metaxas. Bm3e: Discriminative density propagation for visual tracking. PAMI, 2007. 2
    • (2007) PAMI
    • Sminchisescu, C.1    Kanaujia, A.2    Metaxas, D.3
  • 33
    • 84866663472 scopus 로고    scopus 로고
    • An efficient branchand-bound algorithm for optimal human pose estimation
    • 2
    • M. Sun, M. Telaprolu, H. Lee, and S. Savarese. An efficient branchand-bound algorithm for optimal human pose estimation. In CVPR, 2012. 2
    • (2012) CVPR
    • Sun, M.1    Telaprolu, M.2    Lee, H.3    Savarese, S.4
  • 35
    • 77951190698 scopus 로고    scopus 로고
    • Multiple tree models for occlusion and spatial constraints in human pose estimation
    • 2
    • Y. Wang and G. Mori. Multiple tree models for occlusion and spatial constraints in human pose estimation. ECCV, 2008. 2
    • (2008) ECCV
    • Wang, Y.1    Mori, G.2
  • 36
    • 80052895150 scopus 로고    scopus 로고
    • Articulated pose estimation with flexible mixtures-of-parts
    • 2, 3, 4, 5, 6
    • Y. Yang and D. Ramanan. Articulated pose estimation with flexible mixtures-of-parts. In CVPR, 2011. 2, 3, 4, 5, 6
    • (2011) CVPR
    • Yang, Y.1    Ramanan, D.2
  • 37
    • 84880877295 scopus 로고    scopus 로고
    • Action recognition with exemplar based 2. 5 d graph matching
    • 1
    • B. Yao and L. Fei-Fei. Action recognition with exemplar based 2. 5 d graph matching. ECCV, 2012. 1
    • (2012) ECCV
    • Yao, B.1    Fei-Fei, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.