Decision Combination in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine learning of event segmentation for news on demand
Communications of the ACM
Content-based indexing and retrieval of TV news
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
Dialogue Scenes Detection in MPEG Movies: A Multi-expert Approach
MDIC '01 Proceedings of the Second International Workshop on Multimedia Databases and Image Communication
Efficient matching and clustering of video shots
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
Classifying Audio of Movies by a Multi-Expert System
ICIAP '01 Proceedings of the 11th International Conference on Image Analysis and Processing
Efficient MPEG compressed video analysis using macroblock typeinformation
IEEE Transactions on Multimedia
A highly efficient system for automatic face region detection in MPEG video
IEEE Transactions on Circuits and Systems for Video Technology
Automated high-level movie segmentation for advanced video-retrieval systems
IEEE Transactions on Circuits and Systems for Video Technology
Rapid estimation of camera motion from compressed video with application to video annotation
IEEE Transactions on Circuits and Systems for Video Technology
| Hi-index | 0.00 |
In this paper we present a system for movie segmentation based on the automatic detection of dialogue scenes.The proposed system processes the video stream directly in the MPEG domain: it starts with the segmentation of the video footage in shots. Then, a characterization of each shot between dialogue and not-dialogue according to a Multi-Expert System (MES) is performed. Finally, the individuated sequences of shots are aggregated in dialogue scenes by means of a suitable algorithm. The MES integrates three experts, which classifies a given shot on the basis of very complementary descriptions; in particular an audio classifier, a face detector and a camera motion estimator have been built up and employed.The performance of the system have been tested on a huge MPEG movie database made up of more than 15000 shots and 200 scenes, giving rise to encouraging results.