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Volumn 2016-January, Issue , 2016, Pages 3403-3410

Robust joint discriminative feature learning for visual tracking

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; TRACKING (POSITION);

EID: 85006160220     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (77)

References (34)
  • 1
    • 34548412123 scopus 로고    scopus 로고
    • Geometric means in a novel vector space structure on symmetric positive-definite matrices
    • V. Arsigny, P. Fillard, X. Pennec, and N. Ayache. Geometric means in a novel vector space structure on symmetric positive-definite matrices. SIAM J. Matrix Analysis Applications, 29 (1): 328-347, 2006.
    • (2006) SIAM J. Matrix Analysis Applications , vol.29 , Issue.1 , pp. 328-347
    • Arsigny, V.1    Fillard, P.2    Pennec, X.3    Ayache, N.4
  • 5
    • 33645146449 scopus 로고    scopus 로고
    • Histograms of oriented gradients for human detection
    • N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In Proc. CVPR, pages 886-893, 2005.
    • (2005) Proc. CVPR , pp. 886-893
    • Dalal, N.1    Triggs, B.2
  • 6
    • 84937442046 scopus 로고    scopus 로고
    • Online discriminative dictionary learning via label information for multi task object tracking
    • B. Fan, Y. Du, H. Gao, and B. Wang. Online discriminative dictionary learning via label information for multi task object tracking. In Proc. ICME, pages 1-6, 2014.
    • (2014) Proc. ICME , pp. 1-6
    • Fan, B.1    Du, Y.2    Gao, H.3    Wang, B.4
  • 7
    • 33845570001 scopus 로고    scopus 로고
    • On-line boosting and vision
    • H. Grabner and H. Bischof. On-line boosting and vision. In Proc. CVPR, pages 260-267, 2006.
    • (2006) Proc. CVPR , pp. 260-267
    • Grabner, H.1    Bischof, H.2
  • 8
    • 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 Proc. ECCV, pages 234-247, 2008.
    • (2008) Proc. ECCV , pp. 234-247
    • Grabner, H.1    Leistner, C.2    Bischof, H.3
  • 9
    • 77956006668 scopus 로고    scopus 로고
    • Tracking the invisible: Learning where the object might be
    • H. Grabner, J. Matas, L. J. Van Gool, and P. C. Cattin. Tracking the invisible: Learning where the object might be. In Proc. CVPR, pages 1285-1292, 2010.
    • (2010) Proc. CVPR , pp. 1285-1292
    • Grabner, H.1    Matas, J.2    Van Gool, L.J.3    Cattin, P.C.4
  • 10
    • 84856659290 scopus 로고    scopus 로고
    • Struck: Structured output tracking with kernels
    • S. Hare, A. Saffari, and P. H. S. Torr. Struck: Structured output tracking with kernels. In Proc. ICCV, pages 263-270, 2011.
    • (2011) Proc. ICCV , pp. 263-270
    • Hare, S.1    Saffari, A.2    Torr, P.H.S.3
  • 11
    • 84898809070 scopus 로고    scopus 로고
    • Tracking via robust multi-task multi-view joint sparse representation
    • Z. Hong, X. Mei, D. Prokhorov, and D. Tao. Tracking via robust multi-task multi-view joint sparse representation. In Proc. ICCV, pages 649-656, 2013.
    • (2013) Proc. ICCV , pp. 649-656
    • Hong, Z.1    Mei, X.2    Prokhorov, D.3    Tao, D.4
  • 12
    • 84959219372 scopus 로고    scopus 로고
    • Jointly learning heterogeneous features for RGB-D activity recognition
    • J.-F. Hu, W.-S. Zheng, J. Lai, and J. Zhang. Jointly learning heterogeneous features for RGB-D activity recognition. In Proc. CVPR, pages 5344-5352, 2015.
    • (2015) Proc. CVPR , pp. 5344-5352
    • Hu, J.-F.1    Zheng, W.-S.2    Lai, J.3    Zhang, J.4
  • 13
    • 84924666775 scopus 로고    scopus 로고
    • Single and multiple object tracking using a multi-feature joint sparse representation
    • W. Hu, W. Li, X. Zhang, and S. Maybank. Single and multiple object tracking using a multi-feature joint sparse representation. IEEE Trans. Pattern Anal. Mach. Intell., 37 (4): 816-833, 2015.
    • (2015) IEEE Trans. Pattern Anal. Mach. Intell. , vol.37 , Issue.4 , pp. 816-833
    • Hu, W.1    Li, W.2    Zhang, X.3    Maybank, S.4
  • 14
    • 84911449915 scopus 로고    scopus 로고
    • Multi-cue visual tracking using robust feature-level fusion based on joint sparse representation
    • X. Lan, A. J. Ma, and P. C. Yuen. Multi-cue visual tracking using robust feature-level fusion based on joint sparse representation. In Proc. CVPR, pages 1194-1201, 2014.
    • (2014) Proc. CVPR , pp. 1194-1201
    • Lan, X.1    Ma, A.J.2    Yuen, P.C.3
  • 15
    • 84959491321 scopus 로고    scopus 로고
    • Joint sparse representation and robust feature-level fusion for multi-cue visual tracking
    • Dec 2015
    • X. Lan, A. J. Ma, P. C. Yuen, and R. Chellappa. Joint sparse representation and robust feature-level fusion for multi-cue visual tracking. IEEE Trans. Image Process., 24 (12): 5826-5841, Dec 2015.
    • IEEE Trans. Image Process. , vol.24 , Issue.12 , pp. 5826-5841
    • Lan, X.1    Ma, A.J.2    Yuen, P.C.3    Chellappa, R.4
  • 16
    • 85088746113 scopus 로고    scopus 로고
    • Deeptrack: Learning discriminative feature representations by convolutional neural networks for visual tracking
    • H. Li, Y. Li, and F. Porikli. Deeptrack: Learning discriminative feature representations by convolutional neural networks for visual tracking. In Proc. BMVC, 2014.
    • (2014) Proc. BMVC
    • Li, H.1    Li, Y.2    Porikli, F.3
  • 17
    • 0033485370 scopus 로고    scopus 로고
    • Ensemble learning via negative correlation
    • Y. Liu and X. Yao. Ensemble learning via negative correlation. Neural Netw., 12 (10): 1399-1404, 1999.
    • (1999) Neural Netw. , vol.12 , Issue.10 , pp. 1399-1404
    • Liu, Y.1    Yao, X.2
  • 19
    • 80053126093 scopus 로고    scopus 로고
    • Robust visual tracking and vehicle classification via sparse representation
    • X. Mei and H. Ling. Robust visual tracking and vehicle classification via sparse representation. IEEE Trans. Pattern Anal. Mach. Intell., 33 (11): 2259-2272, 2011.
    • (2011) IEEE Trans. Pattern Anal. Mach. Intell. , vol.33 , Issue.11 , pp. 2259-2272
    • Mei, X.1    Ling, H.2
  • 22
    • 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. Vis., 77 (1-3): 125-141, 2008.
    • (2008) Int. J. Comput. Vis. , vol.77 , Issue.1-3 , pp. 125-141
    • Ross, D.A.1    Lim, J.2    Lin, R.-S.3    Yang, M.-H.4
  • 24
    • 33745818927 scopus 로고    scopus 로고
    • Region covariance: A fast descriptor for detection and classification
    • O. Tuzel, F. Porikli, and P. Meer. Region covariance: A fast descriptor for detection and classification. In Proc. ECCV, pages 589-600, 2006.
    • (2006) Proc. ECCV , pp. 589-600
    • Tuzel, O.1    Porikli, F.2    Meer, P.3
  • 25
    • 84973866198 scopus 로고    scopus 로고
    • MMSS: Multi-modal sharable and specific feature learning for rgb-d object recognition
    • A. Wang, J. Cai, J. Lu, and T.-J. Cham. MMSS: Multi-modal sharable and specific feature learning for rgb-d object recognition. In Proc. ICCV, pages 1125-1133, 2015.
    • (2015) Proc. ICCV , pp. 1125-1133
    • Wang, A.1    Cai, J.2    Lu, J.3    Cham, T.-J.4
  • 26
    • 84866709632 scopus 로고    scopus 로고
    • Relaxed collaborative representation for pattern classification
    • M. Yang, D. Zhang, and S. Wang. Relaxed collaborative representation for pattern classification. In Proc. CVPR, pages 2224-2231, 2012.
    • (2012) Proc. CVPR , pp. 2224-2231
    • Yang, M.1    Zhang, D.2    Wang, S.3
  • 27
    • 57149128172 scopus 로고    scopus 로고
    • Online tracking and reacquisition using co-trained generative and discriminative trackers
    • Q. Yu, T. B. Dinh, and G. Medioni. Online tracking and reacquisition using co-trained generative and discriminative trackers. In Proc. ECCV, pages 678-691. 2008.
    • (2008) Proc. ECCV , pp. 678-691
    • Yu, Q.1    Dinh, T.B.2    Medioni, G.3
  • 28
    • 84896063179 scopus 로고    scopus 로고
    • Protein function prediction by integrating multiple kernels
    • G.-X. Yu, H. Rangwala, C. Domeniconi, G. Zhang, and Z. Zhang. Protein function prediction by integrating multiple kernels. In Proc. IJCAI, pages 1869-1875, 2013.
    • (2013) Proc. IJCAI , pp. 1869-1875
    • Yu, G.-X.1    Rangwala, H.2    Domeniconi, C.3    Zhang, G.4    Zhang, Z.5
  • 30
    • 84875236224 scopus 로고    scopus 로고
    • Sparse coding based visual tracking: Review and experimental comparison
    • S. Zhang, H. Yao, X. Sun, and X. Lu. Sparse coding based visual tracking: Review and experimental comparison. Pattern Recognit., 46 (7): 1772-1788, 2013.
    • (2013) Pattern Recognit. , vol.46 , Issue.7 , pp. 1772-1788
    • Zhang, S.1    Yao, H.2    Sun, X.3    Lu, X.4
  • 31
    • 84873114012 scopus 로고    scopus 로고
    • Visual tracking using structured multi-task learning
    • T. Zhang, B. Ghanem, S. Liu, and N. Ahuja. Visual tracking using structured multi-task learning. Int. J. Comput. Vis., 101 (2): 367-383, 2013.
    • (2013) Int. J. Comput. Vis. , vol.101 , Issue.2 , pp. 367-383
    • Zhang, T.1    Ghanem, B.2    Liu, S.3    Ahuja, N.4
  • 32
    • 84960116604 scopus 로고    scopus 로고
    • Online dictionary learning on symmetric positive definite manifolds with vision applications
    • S. Zhang, S. Kasiviswanathan, P. C. Yuen, and M. Harandi. Online dictionary learning on symmetric positive definite manifolds with vision applications. In Proc. AAAI, pages 3165-3173, 2015.
    • (2015) Proc. AAAI , pp. 3165-3173
    • Zhang, S.1    Kasiviswanathan, S.2    Yuen, P.C.3    Harandi, M.4
  • 33
    • 84949783497 scopus 로고    scopus 로고
    • Multi-modality tracker aggregation: From generative to discriminative
    • X. Zhang, W. Li, M. Fan, D. Wang, and X. Ye. Multi-modality tracker aggregation: From generative to discriminative. In Proc. IJCAI, pages 1937-1943, 2015.
    • (2015) Proc. IJCAI , pp. 1937-1943
    • Zhang, X.1    Li, W.2    Fan, M.3    Wang, D.4    Ye, X.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.