Real-time near-duplicate elimination for web video search with content and context

With the exponential growth of social media, there exist huge numbers of near-duplicate web videos, ranging from simple formatting to complex mixture of different editing effects. In addition to the abundant video content, the social web provides rich sets of context information associated with web...

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Main Authors: WU, Xiao, NGO, Chong-wah, HAUPTMANN, Alexander G.
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Language:English
Published: Institutional Knowledge at Singapore Management University 2009
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Online Access:https://ink.library.smu.edu.sg/sis_research/6338
https://ink.library.smu.edu.sg/context/sis_research/article/7341/viewcontent/TMM_Context_wuxiao.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-73412021-11-23T04:30:43Z Real-time near-duplicate elimination for web video search with content and context WU, Xiao NGO, Chong-wah HAUPTMANN, Alexander G. With the exponential growth of social media, there exist huge numbers of near-duplicate web videos, ranging from simple formatting to complex mixture of different editing effects. In addition to the abundant video content, the social web provides rich sets of context information associated with web videos, such as thumbnail image, time duration and so on. At the same time, the popularity of Web 2.0 demands for timely response to user queries. To balance the speed and accuracy aspects, in this paper, we combine the contextual information from time duration, number of views, and thumbnail images with the content analysis derived from color and local points to achieve real-time near-duplicate elimination. The results of 24 popular queries retrieved from You Tube show that the proposed approach integrating content and context can reach real-time novelty re-ranking of web videos with extremely high efficiency, where the majority of duplicates can be rapidly detected and removed from the top rankings. The speedup of the proposed approach can reach 164 times faster than the effective hierarchical method proposed in [31], with just a slight loss of performance. 2009-02-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6338 info:doi/10.1109/TMM.2008.2009673 https://ink.library.smu.edu.sg/context/sis_research/article/7341/viewcontent/TMM_Context_wuxiao.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 Content context copy detection filtering near-duplicates novelty and redundancy detection similarity measure web video 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 Content
context
copy detection
filtering
near-duplicates
novelty and redundancy detection
similarity measure
web video
Graphics and Human Computer Interfaces
spellingShingle Content
context
copy detection
filtering
near-duplicates
novelty and redundancy detection
similarity measure
web video
Graphics and Human Computer Interfaces
WU, Xiao
NGO, Chong-wah
HAUPTMANN, Alexander G.
Real-time near-duplicate elimination for web video search with content and context
description With the exponential growth of social media, there exist huge numbers of near-duplicate web videos, ranging from simple formatting to complex mixture of different editing effects. In addition to the abundant video content, the social web provides rich sets of context information associated with web videos, such as thumbnail image, time duration and so on. At the same time, the popularity of Web 2.0 demands for timely response to user queries. To balance the speed and accuracy aspects, in this paper, we combine the contextual information from time duration, number of views, and thumbnail images with the content analysis derived from color and local points to achieve real-time near-duplicate elimination. The results of 24 popular queries retrieved from You Tube show that the proposed approach integrating content and context can reach real-time novelty re-ranking of web videos with extremely high efficiency, where the majority of duplicates can be rapidly detected and removed from the top rankings. The speedup of the proposed approach can reach 164 times faster than the effective hierarchical method proposed in [31], with just a slight loss of performance.
format text
author WU, Xiao
NGO, Chong-wah
HAUPTMANN, Alexander G.
author_facet WU, Xiao
NGO, Chong-wah
HAUPTMANN, Alexander G.
author_sort WU, Xiao
title Real-time near-duplicate elimination for web video search with content and context
title_short Real-time near-duplicate elimination for web video search with content and context
title_full Real-time near-duplicate elimination for web video search with content and context
title_fullStr Real-time near-duplicate elimination for web video search with content and context
title_full_unstemmed Real-time near-duplicate elimination for web video search with content and context
title_sort real-time near-duplicate elimination for web video search with content and context
publisher Institutional Knowledge at Singapore Management University
publishDate 2009
url https://ink.library.smu.edu.sg/sis_research/6338
https://ink.library.smu.edu.sg/context/sis_research/article/7341/viewcontent/TMM_Context_wuxiao.pdf
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