Double-Ring Mean Shift Algorithm for Visual Tracking
XIA Yu1,2,WU Xiao-Jun1,WANG Hong-Yuan3
1.School of IoT Engineering,Jiangnan University,Wuxi 214122 2.Changshu College,Jiangsu Radio TV University,Changshu 215500 3.School of Information Science Engineering,Changzhou University,Changzhou 213164
Abstract A tracking algorithm based on double-ring Mean Shift is proposed to solve the deficiency of target representation,template similarity measure and fixed kernel-bandwidth in traditional Mean Shift tracking algorithm. The feature extraction model based on universal elliptical region is used to reduce the influence of background feature and improve the quality of target model effectively. Double-ring descriptor is presented to emphasize the importance of target feature and improve the peak modality of matching function. The proposed method updates the bandwidth of kernel-function adaptively by the relationship of double-ring. The experimental results show that the proposed tracking approach is robust and invariant to scale,pose and partial occlusions.
[1] Hou Zhiqiang,Han Chongzhao. A Survey of Visual Tracking. Acta Automatica Sinica,2006,32(4): 603-617 (in Chinese) (候志强,韩崇昭.视觉跟踪技术综述.自动化学报,2006,32(4): 603-617) [2] Babenko B,Yang M H,Belongie S. Robust Object Tracking with Online Multiple Instance Learning. IEEE Trans on Pattern Analysis and Machine Intelligence,2011,33(8): 1619-1632 [3] Datta A,Sheikh Y,Kanade T. Linearized Motion Estimation for Articulated Planes.IEEE Trans on Pattern Analysis and Machine Intelligence,2011,33(4): 780-793 [4] Fukunage K,Hostetler L. The Estimation of The Gradient of A Density Function with Application in Pattern Recognition. IEEE Trans on Information Theory,1975,21(1): 32-40 [5] Cheng Yizong. Mean Shift,Mode Seeking,and Clustering. IEEE Trans on Pattern Analysis and Machine Intelligence,1995,17(8): 790-799 [6] Comaniciu D,Meer P. Mean Shift: A Robust Application toward Feature Space Analysis. IEEE Trans on Pattern Analysis and Machine Intelligence,2002,24(5): 603-619 [7] Birchfield S T,Rangarajan S. Spatiograms versus Histograms for Region-Based Tracking // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. San Diego,USA,2005: 1158-1163 [8] Collins R T,Liu Y,Leordeanu M. Online Selection of Discriminative Tacking Features. IEEE Trans on Pattern Analysis and Machine Intelligence,2005,27(10): 1631-1643 [9] Babu R V,Perez P,Bouthemy P. Robust Tracking with Motion Estimation and Local Kernel-based Color Modeling. Image and Vision Computing,2007,25(8): 1205-1216 [10] Shen Zhixi,Yang Xin,Huang Xiyue. Study on Target Model Update Method in Mean Shift Algorithm. Acta Automatica Sinica,2009,35(5): 478-483 (in Chinese) (沈志熙,杨 欣,黄席樾.均值漂移算法中的目标模型更新方法研究.自动化学报,2009,35(5): 478-483) [11] Qi Zhao,Zhi Yang,Hai Tao.Differential Earth Mover′s Distance with Its Applications to Visual Tracking. IEEE Trans on Pattern Analysis and Machine Intelligence,2010,32(2): 274-287 [12] Li Shuxiao,Chang Hongxing,Zhu Chengfei. Adaptive Pyramid Mean Shift for Global Real-time Visual Tracking. Image and Vision Computing,2010,28(3): 424-437 [13] Chung Y S,Jung S U,Ba Y L,et al. Face Feature Extraction Using Elliptical Model Based Background Deletion and Generalized FEM // Proc of the 3rd International IEEE Conference on Signal-Image Technologies and Internet-Based System. Shanghai,China,2007,IX: 757-762 [14] Birchfield S. An Elliptical Head Tracker // Proc of the 31st Asilomar Conference on Signals,Systems and Computers. Pacific Grove,USA,1997,XI: 1710-1714 [15] Bradski G R. Computer Vision Face Tracking for Use in a Perceptual User Interface // Proc of the 4th IEEE Workshop on Application of Computer Vision. Princeton,USA,1998: 214-219 [16] Collins R T. Mean-Shift Blob Tracking through Scale Space // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. Madison,USA,2003: 234-240 [17] Comaniciu D,Ramesh V,Meer P. Kernel-Based Object Tracking. IEEE Trans on Pattern Analysis and Machine Intelligence,2003,25(5): 564-575 [18] Peng Ningsong,Yang Jie,Liu Zhi,et al. Automatic Selection of Kernel-Bandwidth for Mean-Shift Object Tracking. Journal of Software,2005,16(9): 1542-1550 (in Chinese) (彭宁嵩,杨 杰,刘 志,等.Mean-Shift 跟踪算法中核函数窗宽的自动选取.软件学报,2005,16(9): 1542-1550) [19] Qin Jian,Zheng Xiaoping,Li Yongming. Algorithm of Adaptive Kernel-Bandwidth for Mean-Shift Based on Boundary Force. Journal of Software,2009,20(7): 1726-1734 (in Chinese) (覃 剑,曾孝平,李勇明.基于边界力的Mean-Shift核窗宽自适应算法.软件学报,2009,20(7): 1726-1734) [20]Xia Yu. Research and Application of Visual Tracking. Master Dissertation. Wuxi,China: Jiangnan University,2009 (in Chinese)
2013, Vol. 26 
