Segmentation and Classification of Meeting Events using Multiple Classifier Fusion and Dynamic Programming

In this paper the segmentation of a meeting into meeting events is investigated as well as the recognition of the detected segments. First the classification of a meeting event is examined. Five different classifiers are combined through multiple classifier fusion. Then a way for finding the optimal segment boundaries is presented. With a Dynamic Programming approach quite encouraging results can be obtained. The results show further that by classifier fusion a more stable result can be achieved than using only one single classifier.

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: Gerhard Rigoll, Stephan Reiter
• Keywords: Computer Vision, ICPR 2004, Multiple Classifier Fusion, Optimal Segment Boundaries, Single Classifier