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Automatic content-based retrieval and semantic classification of video content.
- Source :
-
International Journal on Digital Libraries . Feb2006, Vol. 6 Issue 1, p30-38. 9p. 1 Diagram, 4 Charts, 3 Graphs. - Publication Year :
- 2006
-
Abstract
- The problem of video classification can be viewed as discovering the signature patterns in the elemental features of a video class. In order to solve this problem, a large and diverse set of video features is proposed in this paper. The contributions of the paper further lie in dealing with high-dimensionality induced by the feature space and in presenting an algorithm based on two-phase grid searching for automatic parameter selection for support vector machine (SVM). The framework thus is directed to bridge the gap between low-level features and semantic video classes. The experimental results and comparison with state-of-the-art learning tools on more than 5000 video segments show the effectiveness of our approach. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14325012
- Volume :
- 6
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- International Journal on Digital Libraries
- Publication Type :
- Academic Journal
- Accession number :
- 19870612
- Full Text :
- https://doi.org/10.1007/s00799-005-0119-y