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Mean-Shift Tracking Algorithm Based on Adaptive Fusion of Multi-feature
Yang K(杨凯); Xiao YH(肖阳辉); Wang ED(王恩德); Feng JH(冯俊惠)
作者部门光电信息技术研究室
会议名称Conference on Applied Optics and Photonics (AOPC) - Image Processing and Analysis
会议日期MAY 05-07, 2015
会议地点Beijing
会议主办者Chinese Soc Opt Engn, Chinese Soc Astronaut, Photoelectron Technol Comm, Sci & Technol Low Light Level Night Vis Lab, SPIE, Opt Soc, European Opt Soc, Opt Soc Korea
会议录名称Proceedings of SPIE
出版者SPIE-INT SOC OPTICAL ENGINEERING
出版地BELLINGHAM, WA
2015
页码1-6
收录类别EI ; CPCI(ISTP)
EI收录号20161602266861
WOS记录号WOS:000363280200057
产权排序1
ISSN号0277-786X
ISBN号978-1-62841-900-9
关键词Mean-shift Multi-feature Fusion Affine Illumination Model Histogram Of Corner Feature
摘要The classic mean-shift tracking algorithm has achieved success in the field of computer vision because of its speediness and efficiency. However, classic mean-shift tracking algorithm would fail to track in some complicated conditions such as some parts of the target are occluded, little color difference between the target and background exists, or sudden change of illumination and so on. In order to solve the problems, an improved algorithm is proposed based on the mean-shift tracking algorithm and adaptive fusion of features. Color, edges and corners of the target are used to describe the target in the feature space, and a method for measuring the discrimination of various features is presented to make feature selection adaptive. Then the improved mean-shift tracking algorithm is introduced based on the fusion of various features. For the purpose of solving the problem that mean-shift tracking algorithm with the single color feature is vulnerable to sudden change of illumination, we eliminate the effects by the fusion of affine illumination model and color feature space which ensures the correctness and stability of target tracking in that condition. Using a group of videos to test the proposed algorithm, the results show that the tracking correctness and stability of this algorithm are better than the mean-shift tracking algorithm with single feature space. Furthermore the proposed algorithm is more robust than the classic algorithm in the conditions of occlusion, target similar with background or illumination change.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/17203
专题光电信息技术研究室
作者单位1.Shenyang Institute of Automation, Chinese Academy of Science, Shenyang Liaoning, 110016, China
2.University of Chinese Academy of Sciences, Beijing, 100049, China
3.Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Science, Shenyang, Liaoning, 110016, China
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GB/T 7714
Yang K,Xiao YH,Wang ED,et al. Mean-Shift Tracking Algorithm Based on Adaptive Fusion of Multi-feature[C]//Chinese Soc Opt Engn, Chinese Soc Astronaut, Photoelectron Technol Comm, Sci & Technol Low Light Level Night Vis Lab, SPIE, Opt Soc, European Opt Soc, Opt Soc Korea. BELLINGHAM, WA:SPIE-INT SOC OPTICAL ENGINEERING,2015:1-6.
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