메뉴 건너뛰기




Volumn 2015 International Conference on Computer Vision, ICCV 2015, Issue , 2015, Pages 3056-3064

Tracking-by-segmentation with online gradient boosting decision tree

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER VISION; DECISION TREES; TARGET TRACKING; TRACKING (POSITION); TREES (MATHEMATICS);

EID: 84973924437     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2015.350     Document Type: Conference Paper
Times cited : (134)

References (31)
  • 1
    • 77955996634 scopus 로고    scopus 로고
    • A probabilistic framework for joint segmentation and tracking
    • C. Aeschliman, J. Park, and A. C. Kak. A probabilistic framework for joint segmentation and tracking. In CVPR, pages 1371-1378, 2010.
    • (2010) CVPR , pp. 1371-1378
    • Aeschliman, C.1    Park, J.2    Kak, A.C.3
  • 4
    • 84867881463 scopus 로고    scopus 로고
    • Segmentation based particle filtering for real-time 2d object tracking
    • V. Belagiannis, F. Schubert, N. Navab, and S. Ilic. Segmentation based particle filtering for real-time 2d object tracking. In ECCV, pages 842-855, 2012.
    • (2012) ECCV , pp. 842-855
    • Belagiannis, V.1    Schubert, F.2    Navab, N.3    Ilic, S.4
  • 5
    • 84894617371 scopus 로고    scopus 로고
    • Supervised feature learning for curvillinear structure segmentation
    • V. L. C. Becker, R. Rigamonti and P. Fua. Supervised feature learning for curvillinear structure segmentation. In MICCAI, 2013.
    • (2013) MICCAI
    • Becker, V.L.C.1    Rigamonti, R.2    Fua, P.3
  • 6
    • 80052910974 scopus 로고    scopus 로고
    • Context tracker: Exploring supporters and distracters in unconstrained environments
    • T. B. Dinh, N. Vo, and G. Medioni. Context tracker: Exploring supporters and distracters in unconstrained environments. In CVPR, pages 1177-1184, 2011.
    • (2011) CVPR , pp. 1177-1184
    • Dinh, T.B.1    Vo, N.2    Medioni, G.3
  • 7
    • 84898822561 scopus 로고    scopus 로고
    • Pixeltrack: A fast adaptive algorithm for tracking non-rigid objects
    • S. Duffner and C. Garcia. Pixeltrack: A fast adaptive algorithm for tracking non-rigid objects. In ICCV, pages 2480-2487, 2013.
    • (2013) ICCV , pp. 2480-2487
    • Duffner, S.1    Garcia, C.2
  • 9
    • 0035470889 scopus 로고    scopus 로고
    • Greedy function approximation: A gradient boosting machine
    • J. H. Friedman. Greedy function approximation: A gradient boosting machine. Annals of Statistics, 29:1189-1232, 2000.
    • (2000) Annals of Statistics , vol.29 , pp. 1189-1232
    • Friedman, J.H.1
  • 10
    • 84856645114 scopus 로고    scopus 로고
    • Hough-based tracking of non-rigid objects
    • M. Godec, P. M. Roth, and H. Bischof. Hough-based tracking of non-rigid objects. In ICCV, pages 81-88, 2011.
    • (2011) ICCV , pp. 81-88
    • Godec, M.1    Roth, P.M.2    Bischof, H.3
  • 11
    • 84898020313 scopus 로고    scopus 로고
    • Real-time tracking via on-line boosting
    • H. Grabner, M. Grabner, and H. Bischof. Real-time tracking via on-line boosting. In BMVC, page 6, 2006.
    • (2006) BMVC , pp. 6
    • Grabner, H.1    Grabner, M.2    Bischof, H.3
  • 12
    • 56749152262 scopus 로고    scopus 로고
    • Semi-supervised on-line boosting for robust tracking
    • H. Grabner, C. Leistner, and H. Bischof. Semi-supervised on-line boosting for robust tracking. In ECCV, pages 234-247, 2008.
    • (2008) ECCV , pp. 234-247
    • Grabner, H.1    Leistner, C.2    Bischof, H.3
  • 14
    • 61349197458 scopus 로고    scopus 로고
    • Probabilistic fusion-based parameter estimation for visual tracking
    • B. Han and L. S. Davis. Probabilistic fusion-based parameter estimation for visual tracking. Computer Vision and Image Understanding, 113(4):435-445, 2009.
    • (2009) Computer Vision and Image Understanding , vol.113 , Issue.4 , pp. 435-445
    • Han, B.1    Davis, L.S.2
  • 15
    • 84856659290 scopus 로고    scopus 로고
    • Struck: Structured output tracking with kernels
    • S. Hare, A. Saffari, and P. H. Torr. Struck: Structured output tracking with kernels. In ICCV, pages 263-270, 2011.
    • (2011) ICCV , pp. 263-270
    • Hare, S.1    Saffari, A.2    Torr, P.H.3
  • 16
    • 84959254211 scopus 로고    scopus 로고
    • Multi-store tracker (MUSTer): A cognitive psychology inspired approach to object tracking
    • Z. Hong, Z. Chen, C. Wang, X. Mei, D. Prokhorov, and D. Tao. Multi-store tracker (MUSTer): A cognitive psychology inspired approach to object tracking. In CVPR, 2015.
    • (2015) CVPR
    • Hong, Z.1    Chen, Z.2    Wang, C.3    Mei, X.4    Prokhorov, D.5    Tao, D.6
  • 17
    • 84906329965 scopus 로고    scopus 로고
    • Tracking using multilevel quantizations
    • Z. Hong, C. Wang, X. Mei, D. Prokhorov, and D. Tao. Tracking using multilevel quantizations. In ECCV, pages 155-171, 2014.
    • (2014) ECCV , pp. 155-171
    • Hong, Z.1    Wang, C.2    Mei, X.3    Prokhorov, D.4    Tao, D.5
  • 18
    • 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. Vision, 29(1), 1998.
    • (1998) Int. J. Comput. Vision , vol.29 , Issue.1
    • Isard, M.1    Blake, A.2
  • 20
    • 84856684026 scopus 로고    scopus 로고
    • Learning occlusion with likelihoods for visual tracking
    • S. Kwak, W. Nam, B. Han, and J. H. Han. Learning occlusion with likelihoods for visual tracking. In ICCV, pages 1551-1558, 2011.
    • (2011) ICCV , pp. 1551-1558
    • Kwak, S.1    Nam, W.2    Han, B.3    Han, J.H.4
  • 21
    • 56749133171 scopus 로고    scopus 로고
    • Tracking of abrupt motion using wang-landau monte carlo estimation
    • J. Kwon and K. M. Lee. Tracking of abrupt motion using wang-landau monte carlo estimation. In ECCV, pages 387-400, 2008.
    • (2008) ECCV , pp. 387-400
    • Kwon, J.1    Lee, K.M.2
  • 22
    • 70450172803 scopus 로고    scopus 로고
    • Tracking of a non-rigid object via patch-based dynamic appearance modeling and adaptive basin hopping monte carlo sampling
    • J. Kwon and K. M. Lee. Tracking of a non-rigid object via patch-based dynamic appearance modeling and adaptive basin hopping monte carlo sampling. In CVPR, pages 1208-1215, 2009.
    • (2009) CVPR , pp. 1208-1215
    • Kwon, J.1    Lee, K.M.2
  • 23
    • 85097586621 scopus 로고    scopus 로고
    • Robust visual tracking using -1 minimization
    • X. Mei and H. Ling. Robust visual tracking using -1 minimization. In ICCV, pages 1436-1443, 2009.
    • (2009) ICCV , pp. 1436-1443
    • Mei, X.1    Ling, H.2
  • 24
    • 84973920840 scopus 로고    scopus 로고
    • Online graph-based tracking
    • H. Nam, S. Hong, and B. Han. Online graph-based tracking. In ECCV, 2014.
    • (2014) ECCV
    • Nam, H.1    Hong, S.2    Han, B.3
  • 26
    • 39749173057 scopus 로고    scopus 로고
    • Incremental learning for robust visual tracking
    • D. A. Ross, J. Lim, R.-S. Lin, and M.-H. Yang. Incremental learning for robust visual tracking. Int. J. Comput. Vision, 77(1-3):125-141, 2008.
    • (2008) Int. J. Comput. Vision , vol.77 , Issue.1-3 , pp. 125-141
    • Ross, D.A.1    Lim, J.2    Lin, R.-S.3    Yang, M.-H.4
  • 27
    • 12844262766 scopus 로고    scopus 로고
    • GrabCut: Interactive foreground extraction using iterated graph cuts
    • C. Rother, V. Kolmogorov, and A. Blake. GrabCut: interactive foreground extraction using iterated graph cuts. ACM Transactions on Graphics, 23(3):309-314, 2004.
    • (2004) ACM Transactions on Graphics , vol.23 , Issue.3 , pp. 309-314
    • Rother, C.1    Kolmogorov, V.2    Blake, A.3
  • 28
    • 84863041148 scopus 로고    scopus 로고
    • Superpixel tracking
    • S. Wang, H. Lu, F. Yang, and M.-H. Yang. Superpixel tracking. In ICCV, pages 1323-1330, 2011.
    • (2011) ICCV , pp. 1323-1330
    • Wang, S.1    Lu, H.2    Yang, F.3    Yang, M.-H.4
  • 29
    • 84887348427 scopus 로고    scopus 로고
    • Online object tracking: A benchmark
    • Y. Wu, J. Lim, and M.-H. Yang. Online object tracking: A benchmark. In CVPR, pages 2411-2418, 2013.
    • (2013) CVPR , pp. 2411-2418
    • Wu, Y.1    Lim, J.2    Yang, M.-H.3
  • 30
    • 84906331169 scopus 로고    scopus 로고
    • MEEM: Robust tracking via multiple experts using entropy minimization
    • Springer
    • J. Zhang, S. Ma, and S. Sclaroff. MEEM: robust tracking via multiple experts using entropy minimization. In ECCV, pages 188-203. Springer, 2014.
    • (2014) ECCV , pp. 188-203
    • Zhang, J.1    Ma, S.2    Sclaroff, S.3
  • 31
    • 84866648566 scopus 로고    scopus 로고
    • Robust object tracking via sparsity-based collaborative model
    • W. Zhong, H. Lu, and M.-H. Yang. Robust object tracking via sparsity-based collaborative model. In CVPR, pages 1838-1845, 2012.
    • (2012) CVPR , pp. 1838-1845
    • Zhong, W.1    Lu, H.2    Yang, M.-H.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.