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: PENG, Yuxin, NGO, Chong-wah
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2005
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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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spelling sg-smu-ink.sis_research-73232021-11-23T05:11:59Z EMD-based video clip retrieval by many-to-many matching PENG, Yuxin NGO, Chong-wah 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. 2005-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6320 info:doi/10.1007/11526346_11 https://ink.library.smu.edu.sg/context/sis_research/article/7323/viewcontent/CIVR05.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer Sciences Graphics and Human Computer Interfaces
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Computer Sciences
Graphics and Human Computer Interfaces
spellingShingle Computer Sciences
Graphics and Human Computer Interfaces
PENG, Yuxin
NGO, Chong-wah
EMD-based video clip retrieval by many-to-many matching
description 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.
format text
author PENG, Yuxin
NGO, Chong-wah
author_facet PENG, Yuxin
NGO, Chong-wah
author_sort PENG, Yuxin
title EMD-based video clip retrieval by many-to-many matching
title_short EMD-based video clip retrieval by many-to-many matching
title_full EMD-based video clip retrieval by many-to-many matching
title_fullStr EMD-based video clip retrieval by many-to-many matching
title_full_unstemmed EMD-based video clip retrieval by many-to-many matching
title_sort emd-based video clip retrieval by many-to-many matching
publisher Institutional Knowledge at Singapore Management University
publishDate 2005
url 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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