Robust Semantic Concept Detection in Large Video Collections

With explosive amounts of video data emerging from the Internet, automatic video concept detection is becoming very important and has been received great attention. However, reported approaches mainly suffer from low identification accuracy and poor robustness over different concepts. One of the m...

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Main Authors: SHEN, Jialie, Tao, Dacheng, LI, Xuelong
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2009
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Online Access:https://ink.library.smu.edu.sg/sis_research/487
http://dx.doi.org/10.1109/ICSMC.2009.5346651
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-14862010-09-24T06:36:22Z Robust Semantic Concept Detection in Large Video Collections SHEN, Jialie Tao, Dacheng LI, Xuelong With explosive amounts of video data emerging from the Internet, automatic video concept detection is becoming very important and has been received great attention. However, reported approaches mainly suffer from low identification accuracy and poor robustness over different concepts. One of the main reason is that the existing approaches typically isolate the video signature generation from the process of classifier training. Also, very few approaches consider effects of multiple video features. The paper describes a novel approach fusing different information from diverse knowledge sources to facilitate effective video concept detection. The system is designed based on CM*F scheme and its basic architecture contains two core components including 1) CM*F based video signature generation scheme and 2) CM*F based video concept detector. To evaluate the approach proposed, an extensive experimental study on two large video databases has been carried out. The results demonstrate the superiority of the method in terms of effectiveness and robustness. 2009-10-11T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/487 info:doi/10.1109/ICSMC.2009.5346651 http://dx.doi.org/10.1109/ICSMC.2009.5346651 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Detection Information retrieval Video concept Databases and Information Systems Numerical Analysis and Scientific Computing
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Detection
Information retrieval
Video concept
Databases and Information Systems
Numerical Analysis and Scientific Computing
spellingShingle Detection
Information retrieval
Video concept
Databases and Information Systems
Numerical Analysis and Scientific Computing
SHEN, Jialie
Tao, Dacheng
LI, Xuelong
Robust Semantic Concept Detection in Large Video Collections
description With explosive amounts of video data emerging from the Internet, automatic video concept detection is becoming very important and has been received great attention. However, reported approaches mainly suffer from low identification accuracy and poor robustness over different concepts. One of the main reason is that the existing approaches typically isolate the video signature generation from the process of classifier training. Also, very few approaches consider effects of multiple video features. The paper describes a novel approach fusing different information from diverse knowledge sources to facilitate effective video concept detection. The system is designed based on CM*F scheme and its basic architecture contains two core components including 1) CM*F based video signature generation scheme and 2) CM*F based video concept detector. To evaluate the approach proposed, an extensive experimental study on two large video databases has been carried out. The results demonstrate the superiority of the method in terms of effectiveness and robustness.
format text
author SHEN, Jialie
Tao, Dacheng
LI, Xuelong
author_facet SHEN, Jialie
Tao, Dacheng
LI, Xuelong
author_sort SHEN, Jialie
title Robust Semantic Concept Detection in Large Video Collections
title_short Robust Semantic Concept Detection in Large Video Collections
title_full Robust Semantic Concept Detection in Large Video Collections
title_fullStr Robust Semantic Concept Detection in Large Video Collections
title_full_unstemmed Robust Semantic Concept Detection in Large Video Collections
title_sort robust semantic concept detection in large video collections
publisher Institutional Knowledge at Singapore Management University
publishDate 2009
url https://ink.library.smu.edu.sg/sis_research/487
http://dx.doi.org/10.1109/ICSMC.2009.5346651
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