| 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 |
| 引用统计 | |
| 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 |
| 推荐引用方式 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. |
| 条目包含的文件 | 下载所有文件 | |||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Mean-Shift Tracking （231KB） | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 | ||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
修改评论