Trajectories extraction from image sequences based on kinematic

Ghilès Mostafaoui, C. Achard, M. Milgram
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Abstract

The problem of moving person tracking, without knowledge about the number of persons in the scene, and by taking into account occlusion, under-segmentation and over-segmentation, is challenging. A first motion detection gives us regions with several segmentation problems due to bad acquisition conditions. The tracking step, which has to manage all these problems, is realized with the EM algorithm (expectation maximization). It uses a kinematic model: we suppose a rectilinear and uniform apparent motion, this hypothesis seems very restrictive but remains locally accurate in most applications. Good results are obtained with this approach on several sequences, without any initialization.
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基于运动学的图像序列轨迹提取
在不知道场景中有多少人的情况下,并考虑到遮挡、分割不足和过度分割的情况下,移动人员跟踪的问题是具有挑战性的。第一次运动检测给了我们一些由于采集条件不好而存在分割问题的区域。跟踪步骤采用期望最大化算法(EM)实现,该算法需要处理所有这些问题。它使用一个运动学模型:我们假设一个直线和均匀的表观运动,这个假设似乎非常严格,但在大多数应用中仍然是局部准确的。该方法在不进行任何初始化的情况下,对多个序列都得到了较好的结果。
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