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TRACKING OF MOVING OBJECTS BASED ON GRAPH EDGES SIMILARITY

机译:基于图形边缘相似性跟踪移动物体

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This paper suggests a novel contour-based algorithm for tracking moving objects in a video sequence. The algorithm uses the segmentation results of the input frames, which are represented by two region adjacency graphs (RAG) data structures. Based on the image segmentation result, the object's contour is divided into subcurves while junctions of the contour are derived. The junctions are being matched in a search area that is the RAG edges of the consecutive frame. Each pair of matched junctions may be connected by several of paths (edges) that are candidates to represent the tracked contour. Using algorithm for finding the k shortest paths between two nodes these paths are obtained. Then, the construction of the tracked contour is done by a matching process between edges, which are the subcurves, and sets of candidate paths. The use of RAG to construct the tracked contour enables an accurate representation of the moving object while preserving efficient complexity.
机译:本文建议了一种用于跟踪视频序列中的移动对象的基于新型轮廓算法。该算法使用输入帧的分段结果,其由两个区域邻接图(rag)数据结构表示。基于图像分割结果,对象的轮廓被分成亚基,而等高的结来派生。结在作为连续帧的rag边缘的搜索区域中匹配。每对匹配的结可以通过几个路径(边缘)连接,该路径(边缘)是表示跟踪轮廓的候选。使用用于在两个节点之间找到k个最短路径的算法可以获得这些路径。然后,通过边缘之间的匹配过程和候选路径组的匹配过程来完成跟踪轮廓的结构。使用rag构造跟踪轮廓使得能够准确表示移动物体,同时保持有效的复杂性。

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