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| Ball Particle Filter Algorithm for Visual Tracking |
| XIA Yu1,2,WU Xiao-Jun1 |
1.School of Internet of Things Engineering,Jiangnan University,Wuxi 214122
2.Changshu College,Jiangsu Radio and TV University,Changshu 215500 |
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Abstract Particle degeneration is a key issue which influences the performance of a particle filter. To improve the quality of particle sampling and the accuracy of visual tracking, a ball particle filter algorithm for visual tracking is proposed. Ball sampling mode guarantees the valid particles in state-space. Compared to the conventional particle filter, the proposed method uses much fewer particles to ameliorate the diversity of distribution, and overcomes the degeneration problem effectively. By iterative motion of ball, particles are moved towards the regions with larger values of posterior density function. Ball particle filter without depending on state-mode can track the maneuver object with irregular movement. The simulation results show that the proposed method improves the efficiency of particles and achieves fine tracking precision.
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Received: 05 May 2011
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[1] Hou Zhiqiang,Han Chongzhao.A Survey of Visual Tracking.Acta Automatica Sinica,2006,32(4): 603-617 (in Chinese)
(侯志强,韩崇昭.视觉跟踪技术综述.自动化学报,2006,32(4):603-617)
[2] Nejhum S M S,Ho J,Yang M H.Online Visual Tracking with His-
tograms and Articulating Blocks.Computer Vision and Image Understanding,2010,114(8): 901-914
[3] Chu Jinkui,Li Ronghua,Li Qingying,et al.A Visual Attention Model for Robot Object Tracking.International Journal of Automation and Computing,2010,7(1): 39-46
[4] Welch G,Bishop G.An Introduction to the Kalman Filter.Technical Report,TR95- 41.Chapel Hill,USA: University of North Carolina,2004: 1-16
[5] Julier S J,Uhlmann J K.Unscented Filtering and Nonlinear Estimation.Proc of the IEEE,2004,92(3): 401-422
[6] Gustafsson F,Gunnarsson F,Bergman N,et al.Particle Filters for Positioning,Navigation and Tracking.IEEE Trans on Signal Processing,2002,50(2): 425-437
[7] Gordon N J,Salmond D J,Smith A F M.Novel Approach to Nonlinear/Non-Gaussian Bayesian State Estimation.IEEE Proc on Radar and Signal Processing,1993,140(2): 107-113
[8] Hu Shiqiang,Jing Zhongliang.Overview of Particle Filter Algorithm.Control and Decision,2005,20(4):361-365 (in Chinese)
(胡士强,敬忠良.粒子滤波算法综述.控制与决策,2005,20(4):361-365)
[9] Pitt M K,Shephard N.Filtering via Simulation: Auxiliary Particle Filters.Journal of the American Statistical Association,1999,94(446): 590-599
[10] Khan Z,Balch T,Dellaert F.MCMC-Based Particle Filtering for Tracking a Variable Number of Interacting Targets.IEEE Trans on Pattern Analysis and Machine Intelligence,2005,27(11): 1805-1819
[11] Kotecha J H,Djuric P M.Gaussian Particle Filtering.IEEE Trans on Signal Processing,2003,51(10): 2592-2601
[12] Lehn-Schioler T,Erdogmus D,Principe J C.Parzen Particle Filters // Proc of the International Conference on Acoustics,Speech,and Signal Processing.Montreal,Canada,2004,V: 781-784
[13] Bouaynaya N,Schonfeld D.On the Optimality of Motion-Based Particle Filtering.IEEE Trans on Circuits and Systems for Video Technology,2009,19(7): 1068-1072
[14] Derek Y,Reilly J P,Kirubarajan T,et al.Approximate Conditional Mean Particle Filtering for Linear/Nonlinear Dynamic State Space Models.IEEE Trans on Signal Processing,2008,56(12): 5790-5803
[15] Yao Anbang,Wang Guijin,Lin Xinggang,et al.An Incremental Bhattacharyya Dissimilarity Measure for Particle Filtering.Pattern Recognition,2010,43(4): 1244-1256
[16] Campillo F,Rossi V.Convolution Particle Filter for Parameter Estimation in General State-Space Models.IEEE Trans on Aerospace and Electronic Systems,2009,45(3): 1063-1072
[17] Yao Hongge,Qi Hua,Hao Chongyang.Visual Target Tracking Based on the Adaptive Particle Filter in the Complex Situation.Journal of Electronics Information Technology,2009,31(2):275-278 (in Chinese)
(姚红革,齐 华,郝重阳.复杂情形下目标跟踪的自适应粒子滤波算法.电子与信息学报,2009,31(2):275-278) |
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2012, Vol. 25 
