[1] |
Eom K Y, Ahn T K, Kim G J, et al. Fast object tracking in intelligent surveillance system[C]// International Conference on Computational Science and Its Applications. Seoul, Korea: Springer, 2009: 749-763.
|
[2] |
Kettnaker V, Zabih R. Bayesian multi camera surveillance[C]// Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Fort Collins, USA: IEEE Computer Society, 1999: 253-259.
|
[3] |
Shan C F, Tan T N, Wei Y C. Real-time hand tracking using a mean shift embedded particle filter[J]. Pattern Recognition, 2007, 40(7): 1 958-1 970.
|
[4] |
Zhao T, Aggarwal M, Kumar R, et al. Real-time wide area multi-camera stereo tracking[C]// Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego, USA: IEEE Computer Society, 2005: 976-983.
|
[5] |
Siagian C, Itti L. Biologically inspired mobile robot vision localization[J]. IEEE Transactions on Robotics, 2009, 25(4): 861-873.
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[6] |
Yilmaz A, Javed O, Shah M. Object tracking: A survey[J]. ACM Computing Surveys, 2006, 38(4): 1-45.
|
[7] |
Broida T J, Chellappa R. Estimation of object motion parameters from noisy images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(1): 90-99.
|
[8] |
Isard M, Blake A. Condensation-conditional density propagation for visual tracking[J]. International Journal on Computer Vision, 1998, 29(1): 5-28.
|
[9] |
Comaniciu D, Ramesh V, Meer P. Kernel-based object tracking[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(5): 564-577.
|
[10] |
Allen J G, Xu R Y D, Jin J S. Object tracking using CamShift algorithm and multiple quantized feature spaces[C]// Proceedings of the Pan-Sydney Area Workshop on Visual Information Processing. Darlinghurst, Australia: Australia Computer Society, 2004: 3-7.
|
[11] |
Comaniciu D, Ramesh V, Meer P. Real-time tracking of non-rigid objects using mean shift[C]// Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Hilton Head Island, USA: IEEE Computer Society, 2000, 2: 142-149.
|
[12] |
Liu T L, Chen H T. Real-time tracking using trust-region methods[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(3):397-401.
|
[13] |
Hager G D, Belhumeur P N. Efficient region tracking with parametric models of geometry and illumination[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(10): 1 025-1 039.
|
[14] |
Pérez P, Hue C, Vermaak J, et al. Color-based probabilistic tracking[C]// Proceedings of the 7th European Conference on Computer Vision. Copenhagen, Denmark: Springer, 2002: 661-675.
|
[15] |
Reynolds J. Autonomous underwater vehicle: Vision system[D]. Canberra, Australia, Department of Engineering, Australian National University, 1998.
|
[16] |
Ross D A, Lim J, Lin R S, et al. Incremental learning for robust visual tracking[J]. International Journal of Computer Vision, 2008, 77(1-3): 125-141.
|
[17] |
Collins R T, Liu Y X. On-line selection of discriminative tracking features[C]// Proceedings of the 9th IEEE Conference on International Conference on Computer Vision. Nice, France: IEEE Computer Society, 2003: 346-352.
|
[18] |
Nummiaro K, Koller-Meier E, Van Gool L. An adaptive color-based particle filter[J]. Image and Vision Computing, 2003, 21(1): 99-110.
|
[19] |
Ross D, Lim J, Yang M H. Adaptive probabilistic visual tracking with incremental subspace update[C]// Proceedings of the 8th European Conference on Computer Vision. Prague, Czech Republic: Springer, 2004: 470-482.
|
[20] |
Han B, Davis L. On-line density-based appearance modeling for object tracking[C]// Proceedings of the 10th IEEE Conference on International Conference on Computer Vision. Beijing, China: IEEE Computer Society, 2005, 2: 1 492-1 499.
|
[21] |
Zhou Q H, Lu H C, Yang M H. Online multiple support instance tracking[C]// IEEE International Conference on Automatic Face and Gesture Recognition. Santa Barbara, USA: IEEE Computer Society, 2011: 545-552.
|
[22] |
Kwon J, Lee K M. Tracking of a non-rigid object via patch-based dynamic appearance modeling and adaptive basin hopping Monte Carlo sampling[C]// Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Miami, USA: IEEE Computer Society, 2009: 1 208-1 215.
|
[23] |
Sun X, Yao H X, Zhang S P, et al. On-line discriminative appearance modeling for robust object tracking[C]// International Conference on Pervasive Computing Signal Processing and Applications. Harbin, China: IEEE Press, 2010: 78-81.
|
[24] |
Wang Q, Chen F, Xu W L, et al. Online discriminative object tracking with local sparse representation[C]// IEEE Workshop on Applications of Computer Vision. Breckenridge, USA: IEEE Computer Society, 2012: 425-432.
|
[25] |
Jia X, Lu H C, Yang M H. Visual tracking via adaptive structural local sparse appearance model[C]// Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA: IEEE Computer Society, 2012: 1 822-1 829.
|
[26] |
Zhong W, Lu H C, Yang M H. Robust object tracking via sparsity-based collaborative model[C]// Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA: IEEE Computer Society, 2012: 1 838-1 845.
|
[27] |
Frintrop S, Kessel M. Most salient region tracking[C]// IEEE International Conference on Robotics and Automation. Kobe, Japan: IEEE Computer Society, 2009: 1 869-1 874.
|
[28] |
Xu X X, Wang Z L, Chen Z H. Visual tracking model based on feature-imagination and its application[C]// International Conference on Multimedia Information Networking and Security. Nanjing, China: IEEE Computer Society, 2010: 370-374.
|
[29] |
Kong A, Liu J S, Wong W H. Sequential imputations and Bayesian missing data problems[J]. Journal of the American Statistical Association, 1994, 89(425): 278-288.
|
[30] |
Liu J S. Metropolized independent sampling with comparisons to rejection sampling and importance sampling[J]. Statistics and Computing, 1996, 6(2): 113-119.
|
[31] |
Doucet A, Godsill S, Andrieu C. On sequential Monte Carlo sampling methods for Bayesian filtering[J]. Statistics and Computing, 2000, 10(3): 197-208.
|
[32] |
Posner M I, Petersen S E. The attention system of the human brain[J]. Annual Review of Neuroscience, 1990, 13(1): 25-42.
|
[33] |
Liu H, Shi Y. Robust visual tracking based on selective attention shift[C]// IEEE International Conference on Control Applications. Saint Peterburg, Russian: IEEE Press, 2009: 1 176-1 179.
|
[34] |
Zhang G, Yuan Z J, Zheng N N, et al. Visual saliency based object tracking[C]// Proceedings of the 9th Asian Conference on Computer Vision. Xi’an, China: Springer, 2009: 193-203.
|
[35] |
Yang G, Liu H. Visual attention & multi-cue fusion based human motion tracking method[C]// 6th International Conference on Natural Computation. Yantai, China: IEEE Circults And Systems Society, 2010: 2 044-2 054.
|
[36] |
Espinace P, Soto A. Improving the selection and detection of visual landmarks through object tracking[C]// IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Anchroage, AK: IEEE Computer Society, 2008: 1-7.
|
[37] |
朱明清,王智灵,陈宗海. 基于改进Bhattacharyya系数的粒子滤波视觉跟踪算法[J].控制与决策, 2012, 27(10): 1-5.
|
[1] |
Eom K Y, Ahn T K, Kim G J, et al. Fast object tracking in intelligent surveillance system[C]// International Conference on Computational Science and Its Applications. Seoul, Korea: Springer, 2009: 749-763.
|
[2] |
Kettnaker V, Zabih R. Bayesian multi camera surveillance[C]// Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Fort Collins, USA: IEEE Computer Society, 1999: 253-259.
|
[3] |
Shan C F, Tan T N, Wei Y C. Real-time hand tracking using a mean shift embedded particle filter[J]. Pattern Recognition, 2007, 40(7): 1 958-1 970.
|
[4] |
Zhao T, Aggarwal M, Kumar R, et al. Real-time wide area multi-camera stereo tracking[C]// Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego, USA: IEEE Computer Society, 2005: 976-983.
|
[5] |
Siagian C, Itti L. Biologically inspired mobile robot vision localization[J]. IEEE Transactions on Robotics, 2009, 25(4): 861-873.
|
[6] |
Yilmaz A, Javed O, Shah M. Object tracking: A survey[J]. ACM Computing Surveys, 2006, 38(4): 1-45.
|
[7] |
Broida T J, Chellappa R. Estimation of object motion parameters from noisy images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(1): 90-99.
|
[8] |
Isard M, Blake A. Condensation-conditional density propagation for visual tracking[J]. International Journal on Computer Vision, 1998, 29(1): 5-28.
|
[9] |
Comaniciu D, Ramesh V, Meer P. Kernel-based object tracking[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(5): 564-577.
|
[10] |
Allen J G, Xu R Y D, Jin J S. Object tracking using CamShift algorithm and multiple quantized feature spaces[C]// Proceedings of the Pan-Sydney Area Workshop on Visual Information Processing. Darlinghurst, Australia: Australia Computer Society, 2004: 3-7.
|
[11] |
Comaniciu D, Ramesh V, Meer P. Real-time tracking of non-rigid objects using mean shift[C]// Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Hilton Head Island, USA: IEEE Computer Society, 2000, 2: 142-149.
|
[12] |
Liu T L, Chen H T. Real-time tracking using trust-region methods[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(3):397-401.
|
[13] |
Hager G D, Belhumeur P N. Efficient region tracking with parametric models of geometry and illumination[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(10): 1 025-1 039.
|
[14] |
Pérez P, Hue C, Vermaak J, et al. Color-based probabilistic tracking[C]// Proceedings of the 7th European Conference on Computer Vision. Copenhagen, Denmark: Springer, 2002: 661-675.
|
[15] |
Reynolds J. Autonomous underwater vehicle: Vision system[D]. Canberra, Australia, Department of Engineering, Australian National University, 1998.
|
[16] |
Ross D A, Lim J, Lin R S, et al. Incremental learning for robust visual tracking[J]. International Journal of Computer Vision, 2008, 77(1-3): 125-141.
|
[17] |
Collins R T, Liu Y X. On-line selection of discriminative tracking features[C]// Proceedings of the 9th IEEE Conference on International Conference on Computer Vision. Nice, France: IEEE Computer Society, 2003: 346-352.
|
[18] |
Nummiaro K, Koller-Meier E, Van Gool L. An adaptive color-based particle filter[J]. Image and Vision Computing, 2003, 21(1): 99-110.
|
[19] |
Ross D, Lim J, Yang M H. Adaptive probabilistic visual tracking with incremental subspace update[C]// Proceedings of the 8th European Conference on Computer Vision. Prague, Czech Republic: Springer, 2004: 470-482.
|
[20] |
Han B, Davis L. On-line density-based appearance modeling for object tracking[C]// Proceedings of the 10th IEEE Conference on International Conference on Computer Vision. Beijing, China: IEEE Computer Society, 2005, 2: 1 492-1 499.
|
[21] |
Zhou Q H, Lu H C, Yang M H. Online multiple support instance tracking[C]// IEEE International Conference on Automatic Face and Gesture Recognition. Santa Barbara, USA: IEEE Computer Society, 2011: 545-552.
|
[22] |
Kwon J, Lee K M. Tracking of a non-rigid object via patch-based dynamic appearance modeling and adaptive basin hopping Monte Carlo sampling[C]// Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Miami, USA: IEEE Computer Society, 2009: 1 208-1 215.
|
[23] |
Sun X, Yao H X, Zhang S P, et al. On-line discriminative appearance modeling for robust object tracking[C]// International Conference on Pervasive Computing Signal Processing and Applications. Harbin, China: IEEE Press, 2010: 78-81.
|
[24] |
Wang Q, Chen F, Xu W L, et al. Online discriminative object tracking with local sparse representation[C]// IEEE Workshop on Applications of Computer Vision. Breckenridge, USA: IEEE Computer Society, 2012: 425-432.
|
[25] |
Jia X, Lu H C, Yang M H. Visual tracking via adaptive structural local sparse appearance model[C]// Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA: IEEE Computer Society, 2012: 1 822-1 829.
|
[26] |
Zhong W, Lu H C, Yang M H. Robust object tracking via sparsity-based collaborative model[C]// Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA: IEEE Computer Society, 2012: 1 838-1 845.
|
[27] |
Frintrop S, Kessel M. Most salient region tracking[C]// IEEE International Conference on Robotics and Automation. Kobe, Japan: IEEE Computer Society, 2009: 1 869-1 874.
|
[28] |
Xu X X, Wang Z L, Chen Z H. Visual tracking model based on feature-imagination and its application[C]// International Conference on Multimedia Information Networking and Security. Nanjing, China: IEEE Computer Society, 2010: 370-374.
|
[29] |
Kong A, Liu J S, Wong W H. Sequential imputations and Bayesian missing data problems[J]. Journal of the American Statistical Association, 1994, 89(425): 278-288.
|
[30] |
Liu J S. Metropolized independent sampling with comparisons to rejection sampling and importance sampling[J]. Statistics and Computing, 1996, 6(2): 113-119.
|
[31] |
Doucet A, Godsill S, Andrieu C. On sequential Monte Carlo sampling methods for Bayesian filtering[J]. Statistics and Computing, 2000, 10(3): 197-208.
|
[32] |
Posner M I, Petersen S E. The attention system of the human brain[J]. Annual Review of Neuroscience, 1990, 13(1): 25-42.
|
[33] |
Liu H, Shi Y. Robust visual tracking based on selective attention shift[C]// IEEE International Conference on Control Applications. Saint Peterburg, Russian: IEEE Press, 2009: 1 176-1 179.
|
[34] |
Zhang G, Yuan Z J, Zheng N N, et al. Visual saliency based object tracking[C]// Proceedings of the 9th Asian Conference on Computer Vision. Xi’an, China: Springer, 2009: 193-203.
|
[35] |
Yang G, Liu H. Visual attention & multi-cue fusion based human motion tracking method[C]// 6th International Conference on Natural Computation. Yantai, China: IEEE Circults And Systems Society, 2010: 2 044-2 054.
|
[36] |
Espinace P, Soto A. Improving the selection and detection of visual landmarks through object tracking[C]// IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Anchroage, AK: IEEE Computer Society, 2008: 1-7.
|
[37] |
朱明清,王智灵,陈宗海. 基于改进Bhattacharyya系数的粒子滤波视觉跟踪算法[J].控制与决策, 2012, 27(10): 1-5.
|