Adaptive pyramid mean shift for global real-time visual tracking
文献类型：期刊论文
| 作者 | Li, Shu-Xiao ; Chang, Hong-Xing; Zhu, Cheng-Fei
|
| 刊名 | IMAGE AND VISION COMPUTING
 |
| 出版日期 | 2010-03-01 |
| 卷号 | 28期号:3页码:424-437 |
| 关键词 | Global visual tracking Fast mean shift Adaptive level Kernel-based tracking Tracking and pointing subsystem |
| 英文摘要 | Tracking objects in videos using the mean shift technique has attracted considerable attention. In this work, a novel approach for global target tracking based on mean shift technique is proposed. The proposed method represents the model and the candidate in terms of background weighted histogram and color weighted histogram, respectively, which can obtain precise object size adaptively with low computational complexity. To track targets whose displacements between two successive frames are relatively large, we implement the mean shift procedure via a coarse-to-fine way for global maximum seeking. This procedure is termed as adaptive pyramid mean shift, because it uses the pyramid analysis technique and can determine the pyramid level adaptively to decrease the number of iterations required to achieve convergence. Experimental results on various tracking videos and its application to a tracking and pointing subsystem show that the proposed method can successfully cope with different situations such as camera motion, camera vibration, camera zoom and focus, high-speed moving object tracking, partial occlusions, target scale variations, etc. (C) 2009 Elsevier B.V. All rights reserved. |
| WOS标题词 | Science & Technology ; Technology ; Physical Sciences |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Optics |
| 研究领域[WOS] | Computer Science ; Engineering ; Optics |
| 关键词[WOS] | OBJECT TRACKING ; PARTICLE FILTER ; MODE SEEKING ; FEATURES ; COLOR ; SURVEILLANCE ; KERNELS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000273103300013 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/4141]  |
| 专题 | 自动化研究所_综合信息系统研究中心 |
| 作者单位 | Chinese Acad Sci, Inst Automat, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Shu-Xiao,Chang, Hong-Xing,Zhu, Cheng-Fei. Adaptive pyramid mean shift for global real-time visual tracking[J]. IMAGE AND VISION COMPUTING,2010,28(3):424-437. |
| APA | Li, Shu-Xiao,Chang, Hong-Xing,&Zhu, Cheng-Fei.(2010).Adaptive pyramid mean shift for global real-time visual tracking.IMAGE AND VISION COMPUTING,28(3),424-437. |
| MLA | Li, Shu-Xiao,et al."Adaptive pyramid mean shift for global real-time visual tracking".IMAGE AND VISION COMPUTING 28.3(2010):424-437. |
入库方式： OAI收割
来源：自动化研究所
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