| 摘要: |
| 针对Mean-Shift(中值漂移)算法中核函数带宽不能实时改变的缺陷,提出一种基于边界力的Mean-Shift核函数带宽自适应更新算法.在分析目标加权核直方图模型的基础上,引入区域似然度以提取目标的局部信息.然后,比较相邻帧间的区域似然度并构建边界力.通过对边界力的计算,得到边界点的位置,进而自适应地更新核函数带宽.实验结果表明,这些工作改善了Mean-Shift 算法在目标尺度和形态发生变化时的跟踪效果,并且可以满足实时性的需要. |
| 关键词: 中值漂移 目标跟踪 边界力 自适应带宽 |
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| 基金项目:Supported by the National Natural Science Foundation of China under Grant No.30570473 (国家自然科学基金); the DevelopmentFoundation for Information Industry of Chongqing of China under Grant No.20051022 (重庆市信息产业发展基金) |
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| Algorithm of Adaptive Kernel-Bandwidth for Mean-Shift Based on Boundary Force |
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| Abstract: |
| An adaptive scale updating algorithm based on boundary force is presented to improve the deficiency
that the kernel-bandwidth of Mean-Shift is not changeable. Based on the analysis of weighted histogram of the target feature, this paper introduces a region likelihood to extract local information of the target. Then, by comparing the region likelihood in successive frames, it constructs a boundary force to locate the boundary points of the target model and updates the bandwidth of kernel-function adaptively. The experimental results show that the proposed method improves the effect of Mean-Shift when the size or shape of target changes and satisfies the
real-time request. |
| Key words: Mean-Shift object tracking boundary force adaptive bandwidth |
