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News Video Classification Using SVM-based Multimodal Classifiers and Combination Strategies

By Wei-hao Lin

Abstract

Video classification is the first step toward multimedia content understanding. When video is classified into conceptual categories, it is usually desirable to combine evidence from multiple modalities. However, combination strategies in previous studies were usually ad hoc. We investigate a meta-classification combination strategy using Support Vector Machine, and compare it with probability-based strategies. Text features from closedcaptions and visual features from images are combined to classify broadcast news video. The experimental results show that combining multimodal classifiers can significantly improve recall and precision, and our meta-classification strategy gives better precision than the approach of taking the product of the posterior probabilities

Publisher: ACM Press
Year: 2002
OAI identifier: oai:CiteSeerX.psu:10.1.1.19.8225
Provided by: CiteSeerX
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