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 m...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2004
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/6423 |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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. |
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