基于模糊推理背景差结合二次搜索的Camshift自动跟踪算法

Xiao Gang, Chen Yong, Chen Jiu-jun, Gao Fei
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引用次数: 8

摘要

为了克服传统Camshift在跟踪过程中需要人为定位的缺点,提出了一种基于模糊推理背景差分的Camshift跟踪算法。本文采用背景差提取的目标轮廓作为初始搜索窗口,而不是人工选择,实现Camshift自动跟踪。同时,为了避免目标移动过快导致目标发散和目标丢失,两次Camshift搜索结合背景差分自动扩大搜索窗口,保证目标一致。此外,本文还引入了轮廓标记和多Camshift跟踪器来实现成功的多目标跟踪。实验证明,上述方法在跟踪一条或多条运动鱼类方面是有效和自动的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Camshift tracking algorithm based on fuzzy inference background difference combining with twice searching
In order to overcome the shortcoming that traditional Camshift needs artificial orientation during tracking, this paper proposes a new approach of Camshift tracking algorithm based on fuzzy inference background difference. In this paper, the object contour extracted by background difference rather than artificial selection, is used as initial search window so as to realize automatic Camshift tracking. Meanwhile, to avoid object divergence and object losing when the object moves too quickly, twice Camshift searching is combined with background difference to enlarge the search window automatically to ensure consistent targeting. Furthermore, this paper also introduces contour marking and multiple Camshift trackers to implement successful multi-object tracking. Methods mentioned above prove themselves efficient and automatic in tracking one or more moving fishes during the experiments.
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