Effective Video Event Detection Via Subspace Projection
This paper describes a new video event detection framework based on subspace selection technique. With the approach, feature vectors presenting different kinds of video information can be easily projected from different modalities onto an unified subspace, on which recognition process can be perform...
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sg-smu-ink.sis_research-15742010-09-24T08:24:04Z Effective Video Event Detection Via Subspace Projection SHEN, Jialie Tao, Dacheng LI, Xuelong This paper describes a new video event detection framework based on subspace selection technique. With the approach, feature vectors presenting different kinds of video information can be easily projected from different modalities onto an unified subspace, on which recognition process can be performed. The approach is capable of discriminating different classes and preserving the intra-modal geometry of samples within an identical class. Distinguished from the existing multi-modal detection methods, the new system works well when some modalities are not available. Experimental results based on soccer video and TRECVID news video collections demonstrate the effectiveness, efficiency and robustness of the proposed method for individual recognition tasks in comparison to the existing approaches. 2008-01-01T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/575 info:doi/10.1109/MMSP.2008.4665043 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems Numerical Analysis and Scientific Computing |
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Databases and Information Systems Numerical Analysis and Scientific Computing SHEN, Jialie Tao, Dacheng LI, Xuelong Effective Video Event Detection Via Subspace Projection |
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This paper describes a new video event detection framework based on subspace selection technique. With the approach, feature vectors presenting different kinds of video information can be easily projected from different modalities onto an unified subspace, on which recognition process can be performed. The approach is capable of discriminating different classes and preserving the intra-modal geometry of samples within an identical class. Distinguished from the existing multi-modal detection methods, the new system works well when some modalities are not available. Experimental results based on soccer video and TRECVID news video collections demonstrate the effectiveness, efficiency and robustness of the proposed method for individual recognition tasks in comparison to the existing approaches. |
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text |
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SHEN, Jialie Tao, Dacheng LI, Xuelong |
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SHEN, Jialie Tao, Dacheng LI, Xuelong |
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SHEN, Jialie |
title |
Effective Video Event Detection Via Subspace Projection |
title_short |
Effective Video Event Detection Via Subspace Projection |
title_full |
Effective Video Event Detection Via Subspace Projection |
title_fullStr |
Effective Video Event Detection Via Subspace Projection |
title_full_unstemmed |
Effective Video Event Detection Via Subspace Projection |
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effective video event detection via subspace projection |
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Institutional Knowledge at Singapore Management University |
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2008 |
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https://ink.library.smu.edu.sg/sis_research/575 |
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