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Volumn , Issue , 2011, Pages 1201-1208

Globally-optimal greedy algorithms for tracking a variable number of objects

Author keywords

[No Author keywords available]

Indexed keywords

COST FUNCTIONS; IMAGE PROCESSING; PATTERN RECOGNITION; TRACKING (POSITION);

EID: 80052904076     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2011.5995604     Document Type: Conference Paper
Times cited : (834)

References (25)
  • 2
    • 80052913607 scopus 로고    scopus 로고
    • Globally optimal multitarget tracking on a hexagonal lattice
    • A. Andriyenko and K. Schindler. Globally optimal multitarget tracking on a hexagonal lattice. In ECCV, 2010.
    • (2010) ECCV
    • Andriyenko, A.1    Schindler, K.2
  • 5
    • 35148843628 scopus 로고    scopus 로고
    • Fast approximate energy minimization via graph cuts
    • Y. Boykov, O. Veksler, and R. Zabih. Fast approximate energy minimization via graph cuts. IEEE PAMI, 2001.
    • (2001) IEEE PAMI
    • Boykov, Y.1    Veksler, O.2    Zabih, R.3
  • 7
    • 78149335981 scopus 로고    scopus 로고
    • Multiple target tracking in world coordinate with single, minimally calibrated camera
    • W. Choi and S. Savarese. Multiple target tracking in world coordinate with single, minimally calibrated camera. ECCV 2010, pages 553-567, 2010.
    • (2010) ECCV 2010 , pp. 553-567
    • Choi, W.1    Savarese, S.2
  • 9
    • 50249083612 scopus 로고    scopus 로고
    • Depth and appearance for mobile scene analysis
    • A. Ess, B. Leibe, and L. Van Gool. Depth and appearance for mobile scene analysis. In ICCV, 2007.
    • (2007) ICCV
    • Ess, A.1    Leibe, B.2    Van Gool, L.3
  • 10
    • 51949113100 scopus 로고    scopus 로고
    • A discriminatively trained, multiscale, deformable part model
    • P. Felzenszwalb, D. McAllester, and D. Ramanan. A discriminatively trained, multiscale, deformable part model. IEEE CVPR, 2008.
    • (2008) IEEE CVPR
    • Felzenszwalb, P.1    McAllester, D.2    Ramanan, D.3
  • 11
    • 0020782180 scopus 로고
    • Sonar tracking of multiple targets using joint probabilistic data association
    • T. Fortmann, Y. Bar-Shalom, and M. Scheffe. Sonar tracking of multiple targets using joint probabilistic data association. IEEE Journal of Oceanic Engineering, 8(3):173-184, 1983.
    • (1983) IEEE Journal of Oceanic Engineering , vol.8 , Issue.3 , pp. 173-184
    • Fortmann, T.1    Bar-Shalom, Y.2    Scheffe, M.3
  • 12
    • 0001852170 scopus 로고    scopus 로고
    • An efficient implementation of a scaling minimum-cost flow algorithm
    • A. Goldberg. An efficient implementation of a scaling minimum-cost flow algorithm. Journal of Algorithms, 22(1):1-29, 1997.
    • (1997) Journal of Algorithms , vol.22 , Issue.1 , pp. 1-29
    • Goldberg, A.1
  • 13
    • 0034851441 scopus 로고    scopus 로고
    • Bramble: A bayesian multipleblob tracker
    • M. Isard and J. MacCormick. Bramble: A bayesian multipleblob tracker. In ICCV, 2001.
    • (2001) ICCV
    • Isard, M.1    MacCormick, J.2
  • 14
    • 78149344837 scopus 로고    scopus 로고
    • A linear programming approach for multiple object tracking
    • H. Jiang, S. Fels, and J. Little. A linear programming approach for multiple object tracking. In IEEE CVPR, 2007.
    • (2007) IEEE CVPR
    • Jiang, H.1    Fels, S.2    Little, J.3
  • 15
    • 77954605954 scopus 로고
    • The Hungarian method for the assignment problem
    • H. Kuhn, P. Haas, I. Ilyas, G. Lohman, and V. Markl. The Hungarian method for the assignment problem. Masthead, 23(3):151-210, 1993.
    • (1993) Masthead , vol.23 , Issue.3 , pp. 151-210
    • Kuhn, H.1    Haas, P.2    Ilyas, I.3    Lohman, G.4    Markl, V.5
  • 16
    • 50249148608 scopus 로고    scopus 로고
    • Coupled detection and trajectory estimation for multi-object tracking
    • S. K. V. G. L. Leibe, B. Coupled detection and trajectory estimation for multi-object tracking. ICCV 2007.
    • (2007) ICCV
    • Leibe, S.K.V.G.L.1
  • 17
    • 61349113316 scopus 로고    scopus 로고
    • Target tracking with incomplete detection
    • Y. Ma, Q. Yu, and I. Cohen. Target tracking with incomplete detection. CVIU, 2009.
    • (2009) CVIU
    • Ma, Y.1    Yu, Q.2    Cohen, I.3
  • 18
    • 80052913748 scopus 로고    scopus 로고
    • Improving data association by joint modeling of pedestrian trajectories and groupings
    • S. Pellegrini, A. Ess, and L. V. Gool. Improving data association by joint modeling of pedestrian trajectories and groupings. In ECCV, 2010.
    • (2010) ECCV
    • Pellegrini, S.1    Ess, A.2    Gool, L.V.3
  • 19
    • 33845592424 scopus 로고    scopus 로고
    • Multi-object tracking through simultaneous long occlusions and split-merge conditions
    • A. Perera, C. Srinivas, A. Hoogs, G. Brooksby, and W. Hu. Multi-object tracking through simultaneous long occlusions and split-merge conditions. In IEEE CVPR, volume 1, 2006.
    • (2006) IEEE CVPR , vol.1
    • Perera, A.1    Srinivas, C.2    Hoogs, A.3    Brooksby, G.4    Hu, W.5
  • 20
    • 48649093809 scopus 로고    scopus 로고
    • Evaluation of algorithms for tracking multiple objects in video
    • A. G. A. Perera, A. Hoogs, C. Srinivas, G. Brooksby, and W. Hu. Evaluation of algorithms for tracking multiple objects in video. In AIPR, page 35, 2006.
    • (2006) AIPR , pp. 35
    • Perera, A.G.A.1    Hoogs, A.2    Srinivas, C.3    Brooksby, G.4    Hu, W.5
  • 23
    • 80052876289 scopus 로고    scopus 로고
    • Multi-object tracking through occlusions by local tracklets filtering and global tracklets association with detection responses
    • June
    • J. Xing, H. Ai, and S. Lao. Multi-object tracking through occlusions by local tracklets filtering and global tracklets association with detection responses. In IEEE CVPR, June 2009.
    • (2009) IEEE CVPR
    • Xing, J.1    Ai, H.2    Lao, S.3
  • 25
    • 51949088494 scopus 로고    scopus 로고
    • Global data association for multi-object tracking using network flows
    • L. Zhang, Y. Li, and R. Nevatia. Global data association for multi-object tracking using network flows. In CVPR, 2008.
    • (2008) CVPR
    • Zhang, L.1    Li, Y.2    Nevatia, R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.