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A novel trajectory pattern learning method based on vector quantization and depth first search
基于矢量量化和深度优先搜索的轨迹分布模式学习算法

Keywords: trajectory analysis and learning,vector quantization,depth first search
轨迹分析与学习
,矢量量化,深度优先搜索,矢量量化,深度优先搜索,轨迹,分布模式,学习算法,depth,first,search,vector,quantization,based,learning,method,pattern,trajectory,异常行为检测,目标,复杂场景,应用,时序关系,检测方法,实验,序列图像,序列模式图

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Abstract:

This paper puts forward a novel depth first search method to learning the distribution of motion trajectory based on the vector quantization of the flow vectors.Then the sequential patterns graph is generated,which visually represents the trajectory pattern.The corresponding anomaly detection method is also given in this paper.The experiments on different sites demonstrate that our method can not only discover the flow vector's distribution but also can reflect their time orders effectively, which makes it suitable for anomaly detection in outdoor scenes.

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