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An improved Mean-shift tracking algorithm based on
color and texture feature |
| DAI Yuan-ming, WEI Wei, LIN Yi-ning |
| College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China |
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Abstract Aimed at the defect of classic Mean-shift tracking algorithm which is vulnerable to similar background inference for using single color feature, an improved color and texture features combined Mean-shift tracking algorithm is presented. Feature joint similarity was introduced for the first time. By maximizing the integrated similarity using Mean-shift algorithm the center of target in the new frame can be obtained accurately and rapidly. Experiments show that the proposed algorithm provides more reliable performance while satisfying the real-time requirements of general target tracking tasks.
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Published: 20 March 2012
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基于颜色纹理特征的均值漂移目标跟踪算法
针对经典均值漂移跟踪算法采用单一的颜色特征对目标进行跟踪检测存在的不足，提出一种将纹理特征与颜色特征相结合的改进均值漂移目标跟踪算法.该算法首次提出特征联合相似度的概念，通过均值漂移算法联合相似度的最大化计算，正确快速地获取新一帧图像跟踪目标的位置.实验结果表明，该算法具有更高的可靠性，同时满足一般目标跟踪任务的实时性要求.
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| ［1］ DRUMMOND T, CIPOLLA R. Realtime visual tracking of complex structures ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 4(7): 932-946.
［2］ COMANICIU D, RAMESH V, MEER P. Kernelbased object tracking ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(5): 564-577.
［3］ LIU T L, CHEN H T. Realtime tracking using trustregion methods ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(3): 397-402.
［4］ COLLINS R T. Meanshift blob tracking through scale space ［C］∥ Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Madison Wisconsin: IEEE CS, 2003, 2: 234-240.
［5］ ZIVKOVIC Z, KROSE B. An EMlike algorithm for colorhistogrambased object tracking ［C］∥ Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Washirgton D. C.: IEEE CS, 2004: 798-803.
［6］ STERN H, EFROS B. Adaptive color space switching for face tracking in multicolor lighting environment ［C］∥ Proceedings of IEEE Conference on Automatice Face and Gesture Recognition. Washirgton D. C.: IEEE CS,2002: 249-254.
［7］ COLLINS R T, LIU Y. Online selection of discriminative tracking features ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(10): 1631-1643.
［8］ POLAT E, OZDEN. Anonparametric adaptive tracking algorithm based on multiple feature distributions ［J］. IEEE Transactions on Multimedia, 2006, 8: 1156-1163.
［9］ WANG J Q, YAGI Y. Integrating shape and color features for adaptive realtime object tracking ［C］∥ Proceedings of IEEE Conference on Robotics and Biomimetics. Kunming: IEEE RAS, 2006: 1-6.
［10］ TUCERYAN M, JAIN A K. Texture analysis, handbook pattern recognition and computer vision ［M］. Singapore: World Scientific, 1993: 235-276.
［11］ STOLLNITZ E J, DEROSE T D, SALESIN D H. Wavelets for computer graphics: A primer part 1 ［J］ IEEE Computer Graphics and Application, 1995, 15: 76-84.
［12］ MANJUNATH B S, MA W Y. Texture features for browsing andretrieval of large imagedata ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996, 18(8): 837-842.
［13］ KARASARIDIS A, SIMONCELLI E. A filter design technique for steerable pyramid image transforms ［C］∥ Proceedings of International Conference on Acoustics Speech and Signal Processing. Atlanta, Georgia: IEEE SPS, 1996: 2387-2390. |
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