EMD-based video clip retrieval by many-to-many matching
This paper presents a new approach for video clip retrieval based on Earth Mover's Distance (EMD). Instead of imposing one-to-one matching constraint as in [11, 14], our approach allows many-to-many matching methodology and is capable of tolerating errors due to video partitioning and various v...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2005
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/6320 https://ink.library.smu.edu.sg/context/sis_research/article/7323/viewcontent/CIVR05.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | This paper presents a new approach for video clip retrieval based on Earth Mover's Distance (EMD). Instead of imposing one-to-one matching constraint as in [11, 14], our approach allows many-to-many matching methodology and is capable of tolerating errors due to video partitioning and various video editing effects. We formulate clip-based retrieval as a graph matching problem in two stages. In the first stage, to allow the matching between a query and a long video, an online clip segmentation algorithm is employed to rapidly locate candidate clips for similarity measure. In the second stage, a weighted graph is constructed to model the similarity between two clips. EMD is proposed to compute the minimum cost of the weighted graph as the similarity between two clips. Experimental results show that the proposed approach is better than some existing methods in term of ranking capability. |
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