Clustering-Based Analysis of Semantic Concept Models for Video Shots

Markus Koskela and Alan F. Smeaton. In Proceedings of IEEE International Conference on Multimedia & Expo (ICME 2006). Toronto, Ontario, Canada. July 2006.

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In this paper we present a clustering-based method for representing semantic concepts on multimodal low-level feature spaces and study the evaluation of the goodness of such models with entropy-based methods. As different semantic concepts in video are most accurately represented with different features and modalities, we utilize the relative model-wise confidence values of the feature extraction techniques in weighting them automatically. The method also provides a natural way of measuring the similarity of different concepts in a multimedia lexicon. The experiments of the paper are conducted using the development set of the TRECVID 2005 corpus together with a common annotation for 39 semantic concepts.