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Automatic Adaptive Segmentation of Moving Objects Based on Spatio-Temporal Information

机译:基于时空信息的移动对象自动分割

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This paper suggests a novel segmentation algorithm for separating moving objects from the background in video sequences without any prior information of the sequence nature. We formulate the problem as a connectivity analysis of region adjacency graph (RAG) based on temporal information. The nodes of the RAG represent homogeneous regions and the edges represent temporal information, which is obtained by frames comparison iterations. Connectivity analysis of the RAG nodes is performed after each frames comparison by a breadth first search (BFS) based algorithm. The set of nodes, which achieve maximum weight of theirs surrounding edges are considered as moving object. The number of comparisons that are needed for temporal information is automatically determined.
机译:本文建议一种新的分段算法,用于将移动物体从视频序列中的背景分离,而无需序列性的任何先前信息。我们根据时间信息作为区域邻接图(RAG)的连接分析。 rag的节点代表均匀区域,边缘代表由帧比较迭代获得的时间信息。在每个帧由基于广度第一搜索(BFS)的算法的每个帧比较之后执行RAG节点的连接性分析。达到周围边缘最大重量的节点集被认为是移动对象。自动确定时间信息所需的比较次数。

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