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Using High-Level Semantic Features in Video Retrieval.

Authors :
Sundaram, Hari
Naphade, Milind
Smith, John R.
Yong Rui
Wujie Zheng
Jianmin Li
Zhangzhang Si
Fuzong Lin
Bo Zhang
Source :
Image & Video Retrieval (9783540360186); 2006, p370-379, 10p
Publication Year :
2006

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540360186
Database :
Supplemental Index
Journal :
Image & Video Retrieval (9783540360186)
Publication Type :
Book
Accession number :
32703103
Full Text :
https://doi.org/10.1007/11788034_38