Abstract
Extraction and utilization of high-level semantic features are critical for more effective video retrieval. However, the performance of video retrieval hasn’t benefited much despite of the advances in high-level feature extraction. To make good use of high-level semantic features in video retrieval, we present a method called pointwise mutual information weighted scheme(PMIWS). The method makes a good judgment of the relevance of all the semantic features to the queries, taking the characteristics of semantic features into account. The method can also be extended for the fusion of multi-modalities. Experiment results based on TRECVID2005 corpus demonstrate the effectiveness of the method.
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Zheng, W., Li, J., Si, Z., Lin, F., Zhang, B. (2006). Using High-Level Semantic Features in Video Retrieval. In: Sundaram, H., Naphade, M., Smith, J.R., Rui, Y. (eds) Image and Video Retrieval. CIVR 2006. Lecture Notes in Computer Science, vol 4071. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11788034_38
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DOI: https://doi.org/10.1007/11788034_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36018-6
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