| Y. Avrithis, A. Doulamis, N. Doulamis and S. Kollias |
| A Stochastic Framework for Optimal Key Frame Extraction from MPEG Video Databases |
| Computer Vision and Image Understanding, vol. 75 (1/2), pp. 3-24, July 1999. |
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ABSTRACT
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| A video content representation framework is proposed in this paper for extracting limited, but meaningful, information of video data, directly from the MPEG compressed domain. A hierarchical color and motion segmentation scheme is applied to each video shot, transforming the frame-based representation to a feature-based one. The scheme is based on a multiresolution implementation of the recursive shortest spanning tree (RSST) algorithm. Then, all segment features are gathered together using a fuzzy multidimensional histogram to reduce the possibility of classifying similar segments to different classes. Extraction of several key frames is performed for each shot in a content-based rate-sampling framework. Two approaches are examined for key frame extraction. The first is based on examination of the temporal variation of the feature vector trajectory; the second is based on minimization of a cross-correlation criterion of the video frames. For efficient implementation of the latter approach, a logarithmic search (along with a stochastic version) and a genetic algorithm are proposed. Experimental results are presented which illustrate the performance of the proposed techniques, using synthetic and real life MPEG video sequences.
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| 01 July , 1999 |
| Y. Avrithis, A. Doulamis, N. Doulamis and S. Kollias, "A Stochastic Framework for Optimal Key Frame Extraction from MPEG Video Databases", Computer Vision and Image Understanding, vol. 75 (1/2), pp. 3-24, July 1999. |
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