| 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)
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| Department | 光电信息技术研究室 |
| Conference Name | Conference on Applied Optics and Photonics (AOPC) - Image Processing and Analysis |
| Conference Date | MAY 05-07, 2015 |
| Conference Place | Beijing |
| Author of Source | 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 |
| Source Publication | Proceedings of SPIE |
| Publisher | SPIE-INT SOC OPTICAL ENGINEERING |
| Publication Place | BELLINGHAM, WA |
| 2015 | |
| Pages | 1-6 |
| Indexed By | EI ; CPCI（ISTP） |
| EI Accession number | 20161602266861 |
| WOS ID | WOS:000363280200057 |
| Contribution Rank | 1 |
| ISSN | 0277-786X |
| ISBN | 978-1-62841-900-9 |
| Keyword | Mean-shift Multi-feature Fusion Affine Illumination Model Histogram Of Corner Feature |
| Abstract | 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. |
| Language | 英语 |
| Citation statistics | |
| Document Type | 会议论文 |
| Identifier | http://ir.sia.cn/handle/173321/17203 |
| Collection | 光电信息技术研究室 |
| Affiliation | 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 |
| Recommended Citation 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. |
| Files in This Item: | Download All | |||||
| File Name/Size | DocType | Version | Access | License | ||
| Mean-Shift Tracking （231KB） | 会议论文 | 开放获取 | CC BY-NC-SA | View Download | ||
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