基于多特征融合的Mean Shift跟踪算法

倪琦; 贺明; 张国进; 张鼎; 朱晓卿

doi:10.11884/HPLPB201426.101022

强激光与粒子束

基于多特征融合的Mean Shift跟踪算法

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倪琦, 贺明, 张国进, 张鼎, 朱晓卿. 2014: 基于多特征融合的Mean Shift跟踪算法, 强激光与粒子束, null(10): 101022. doi: 10.11884/HPLPB201426.101022

引用本文:

倪琦, 贺明, 张国进, 张鼎, 朱晓卿. 2014: 基于多特征融合的Mean Shift跟踪算法, 强激光与粒子束, null(10): 101022. doi: 10.11884/HPLPB201426.101022

Ni Qi, He Ming, Zhang Guojin, Zhang Ding, Zhu Xiaoqing. 2014: Tracking algorithm based on multi-feature fusion Mean Shift, High Power Lase and Particle Beams, null(10): 101022. doi: 10.11884/HPLPB201426.101022

Citation:

Ni Qi, He Ming, Zhang Guojin, Zhang Ding, Zhu Xiaoqing. 2014: Tracking algorithm based on multi-feature fusion Mean Shift, High Power Lase and Particle Beams, null(10): 101022. doi: 10.11884/HPLPB201426.101022

基于多特征融合的Mean Shift跟踪算法

解放军 63983 部队,江苏无锡,214083
解放军信息工程大学,郑州,450052

Tracking algorithm based on multi-feature fusion Mean Shift

摘要: 在对 Mean Shift跟踪算法原理分析的基础上提出了一种反映区域像素空间关系的特征值与原算法基核结合的跟踪方式。该方式采用适应性公式与相似性量度结合的二级判决策略，提取区域内特征值并按不同权重归一化特征值。若不满足特征观测值的条件，则采取粗-精搜索结合的方式对目标模型进行更新。实验结果表明目标跟踪过程中提取的特征值波动符合目标区域实际情况，并在波动异常时重新定位目标，从而提高了跟踪的稳定性。
- 空间关系 /
- 相似性量度 /
- 目标区域 /
- 跟踪
Abstract: A tracking mode is presented which reflects regional pixel spatial relationship combining with the core of the orig-inal algorithm based on the analysis of the principle of algorithm.Meanwhile the adaptability and the similarity measure formula with two level decision strategy are adopted,and it extracted region characteristic to normalize values by the different right.If it does not meet the characteristics of observed value condition,the coarse-fine search to update the target model should be adopted. Experimental results show that the fluctuations characteristic observations meet the actual situation of the target area in the target tracking process,and the target in the case of abnormal fluctuations can be repositioned,thereby the tracking stability can be im-proved.

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基于多特征融合的Mean Shift跟踪算法

解放军 63983 部队,江苏无锡,214083
解放军信息工程大学,郑州,450052

关键词:

摘要: 在对 Mean Shift跟踪算法原理分析的基础上提出了一种反映区域像素空间关系的特征值与原算法基核结合的跟踪方式。该方式采用适应性公式与相似性量度结合的二级判决策略，提取区域内特征值并按不同权重归一化特征值。若不满足特征观测值的条件，则采取粗-精搜索结合的方式对目标模型进行更新。实验结果表明目标跟踪过程中提取的特征值波动符合目标区域实际情况，并在波动异常时重新定位目标，从而提高了跟踪的稳定性。

English Abstract

Tracking algorithm based on multi-feature fusion Mean Shift

解放军 63983 部队,江苏无锡,214083
解放军信息工程大学,郑州,450052

Keywords:

Abstract: A tracking mode is presented which reflects regional pixel spatial relationship combining with the core of the orig-inal algorithm based on the analysis of the principle of algorithm.Meanwhile the adaptability and the similarity measure formula with two level decision strategy are adopted,and it extracted region characteristic to normalize values by the different right.If it does not meet the characteristics of observed value condition,the coarse-fine search to update the target model should be adopted. Experimental results show that the fluctuations characteristic observations meet the actual situation of the target area in the target tracking process,and the target in the case of abnormal fluctuations can be repositioned,thereby the tracking stability can be im-proved.

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基于多特征融合的Mean Shift跟踪算法

Tracking algorithm based on multi-feature fusion Mean Shift

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基于多特征融合的Mean Shift跟踪算法

English Abstract

Tracking algorithm based on multi-feature fusion Mean Shift

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