首页> 外文会议>Biennial Australian Pattern Recognition Society Conference(DICTA2003) v.2; 2003; Sydney; AU >Automatic Adaptive Segmentation of Moving Objects Based on Spatio-Temporal Information
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Automatic Adaptive Segmentation of Moving Objects Based on Spatio-Temporal Information

机译:基于时空信息的运动目标自动自适应分割

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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:本文提出了一种新颖的分割算法,该算法可将视频序列中的运动对象从背景中分离出来,而无需任何先验的序列性质信息。我们将问题表达为基于时间信息的区域邻接图(RAG)的连通性分析。 RAG的节点代表同质区域,边缘代表时间信息,这些信息是通过帧比较迭代获得的。在每个帧比较之后,通过基于广度优先搜索(BFS)的算法对RAG节点进行连通性分析。达到其周围边缘最大权重的那组节点被视为运动对象。时间信息所需的比较次数会自动确定。

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