%0 Journal Article %A Chen, Ming-yu %A Hauptmann, Alexander %D 1993 %T Active Learning in Multiple Modalities for Semantic Feature Extraction from Video %U https://kilthub.cmu.edu/articles/journal_contribution/Active_Learning_in_Multiple_Modalities_for_Semantic_Feature_Extraction_from_Video/6602966 %R 10.1184/R1/6602966.v1 %2 https://kilthub.cmu.edu/ndownloader/files/12093023 %K computer sciences %X Active learning has been demonstrated to be a useful tool to reduce human labeling effort for many multimedia applications. However, most of the previous work on multimedia active learning has gloss the multi-modality problem very much. From several experimental results, multi-modality fusion plays an important role to boost performance of multimedia classification. In this paper, we present a multi-modality active learning approach which enhances the process of active learning approach from single-modality to multi-modality. The experimental results on the TRECVID 2004 semantic feature extraction task show that the proposed active learning approach works more effectively than single-modality approach and also demonstrate a significantly reduced amount of labeled data. %I Carnegie Mellon University