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Abstract

This paper proposes a novel approach to extract meaningful content information from video by collaborative integration of image understanding and natural language processing. As an actual example, we developed a system that associates faces and names in videos, called Name-It, which is given news videos as a knowledge source, then automatically extracts face and name association as content information. The system can infer the name of a given unknown face image, or guess faces which are likely to have the name given to the system. This paper explains the method with several successful matching results which reveal effectiveness in integrating heterogeneous techniques as well as the importance of real content information extraction from video, especially face-name association.

Notes

Text Reference

Shin'ichi Satoh and Takeo Kanade, "Name-It: Association of Face and Name in Video," Proceedings of 1997 IEEE Computer Vision and Pattern Recognition (CVPR '97), June, 1997, pp. 368-373.

BibTeX Reference

@inproceedings{Kanade_1997_995,
   author = "Shin'ichi Satoh and Takeo Kanade",
   title = "Name-It: Association of Face and Name in Video",
   booktitle = "Proceedings of 1997 IEEE Computer Vision and Pattern Recognition (CVPR '97)",
   pages = "368-373",
   month = "June",
   year = "1997",
}

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