A robust dissolve detector by support vector machine
In this paper, we propose a novel approach for the robust detection and classification of dissolve sequences in videos. Our approach is based on the multi-resolution representation of temporal slices extracted from 3D image volume. At the low-resolution (LR) scale, the problem of dissolve detection...
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| 格式: | text |
| 語言: | English |
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Institutional Knowledge at Singapore Management University
2003
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| 主題: | |
| 在線閱讀: | https://ink.library.smu.edu.sg/sis_research/6454 https://ink.library.smu.edu.sg/context/sis_research/article/7457/viewcontent/957013.957072.pdf |
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| 機構: | Singapore Management University |
| 語言: | English |
| 總結: | In this paper, we propose a novel approach for the robust detection and classification of dissolve sequences in videos. Our approach is based on the multi-resolution representation of temporal slices extracted from 3D image volume. At the low-resolution (LR) scale, the problem of dissolve detection is reduced as cut transition detection. At the highresolution (HR) space, Gabor wavelet features are computed for regions that surround the cuts located at LR scale. The computed features are then input to support vector machines for pattern classification. Encouraging results have been obtained through experiments. |
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