一种基于二分图最优匹配的镜头检索方法

镜头检索是基于内容的视频检索的重要内容.本文首次尝试将二分图的最优匹配用于镜头检索.与现有方法相比,本文提出的方法强调在一一对应的前提下,全面客观地度量两个镜头的相似度.把两个镜头的相似度度量建模为一个带权的二分图:镜头中的每一帧看成二分图的一个结点,两个镜头之间任意帧的相似值作为边的权值.在一一对应的前提下,利用最优匹配的Kuhn-Munkres算法求出该二分图的最大权,以此作为两个镜头的相似度.考虑到检索速度问题,提出了两个改进算法.实验对比结果证实了本文所提方法在镜头检索中的优异表现.

An Approach for Shot Retrieval by Optimal Matching in the Bipartite Graph

Shot retrieval plays a critical role in content based video retrieval.Motivated by the theory of optimal matching in bipartite graph,we propose a novel approach based on the Kuhn Munkres algorithm for shot retrieval.In contrast to existing algorithms,the proposed approach emphasizes one to one mapping among frames between two shots for effective similarity measure.A weighted bipartite graph is constructed to model the similarity between two shots:every vertex in a bipartite graph represents one frame in a shot,and the weight of every edge represents the similarity value for a pair of frames between two shots.Then Kuhn Munkres algorithm is employed to compute the maximum weight of a constructed bipartite graph as the similarity value between two shots by guaranteeing the one to one mapping among frames.To improve the speed efficiency,we also propose two improved algorithms.Experimental results indicate that the proposed approach achieves superior performance than some existing methods.