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A particle filter object tracking based on feature and location fusion

机译：基于特征和位置融合的粒子滤波对象跟踪

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摘要

For the object tracking under complex scenes, this paper proposes a tracking algorithm combining both the sample feature and the location. According to differences between the object and its neighboring background in different color subspaces, the suitable color subspaces, which make the object outstanding from the background, are selected and the multiple feature descriptions based on the selected color subspace are produced to represent the object. Thus, under the particle filter framework, the similarity matrix which is based on the sample feature and the location are computed. According to the similarity matrix, the algorithm determine the final object location. The results show the proposed algorithm realizes the robustness of the video object tracking to some extent.
机译：对于复杂场景下的目标跟踪，提出了一种结合样本特征和位置的跟踪算法。根据对象及其相邻背景在不同颜色子空间中的差异，选择使对象相对于背景突出的合适颜色子空间，并基于所选颜色子空间生成多个特征描述以表示对象。因此，在粒子过滤器框架下，计算基于样本特征和位置的相似度矩阵。根据相似度矩阵，算法确定最终的对象位置。结果表明，该算法在一定程度上实现了视频目标跟踪的鲁棒性。

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