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A Robust Dissolve Detector By Support Vector Machine, Chong-Wah Ngo
A Robust Dissolve Detector By Support Vector Machine, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
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.