Knowledge Commons of Institute of Automation,CAS
Multi-Information Fusion for Scale Selection in Robot Tracking | |
Zhang, Xiaoqin![]() ![]() ![]() | |
2006 | |
会议名称 | IEEE/RSJ International Conference on Intelligent Robots and Systems |
会议录名称 | 2006 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS |
会议日期 | OCT 09-13, 2006 |
会议地点 | Beijing, PEOPLES R CHINA |
摘要 | Mean shift, for its simplicity and efficiency, has achieved a considerable success in robot tracking. For the mean shift based tracking algorithm, the scale of the mean-shift kernel bandwidth is a crucial parameter which reflects the size of tracking window. However, in literature how to properly update or select the bandwidth remains a tough task as the size of the object under consideration changes. In this paper, a weighted average integral projection approach is proposed to extract the local information of the object, and then a multi-information fusion strategy is suggested for the scale selection, which combines both the global and local information of the sample weight image. Moreover, a coarse-to-fine approximate approach is employed to accelerate the procedure. Experimental results demonstrate that, compared to some existing works, the strategy proposed has a better adaptability as the size of the object changes in clutter environments. |
关键词 | Mean Shift Integral Projection Kernel Bandwidth |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/12824 |
专题 | 多模态人工智能系统全国重点实验室_机器人理论与应用 |
通讯作者 | Zhang, Xiaoqin) |
作者单位 | Chinese Acad Sci, Inst Automat |
推荐引用方式 GB/T 7714 | Zhang, Xiaoqin,Qiao, Hong,Liu, Zhiyong,et al. Multi-Information Fusion for Scale Selection in Robot Tracking[C],2006. |
条目包含的文件 | 条目无相关文件。 |
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