NDLI: Construction of Semantic Network for Videos

Content Provider	IEEE Xplore Digital Library
Author	Wang Fangshi Xu De Xu Hongli Wu Weixin
Copyright Year	2006
Description	Author affiliation: Sch. of Comput. & Inf. Technol., Beijing Jiaotong Univ. (Wang Fangshi; Xu De; Xu Hongli; Wu Weixin)
Abstract	Annotating videos manually is very costly and time consuming. Human being's subjective and different understanding often lead to incomplete and inconsistent annotations and poor system performance. So it is an importance topic to annotate automatically semantic concepts for a video. Discovering the relationships among several concepts coexisting in the same video can help automatic semantic annotation. In this paper, we propose an improved K2 algorithm to learn the structure of the semantic network based Bayesian network. Its advantage over original K2 algorithm is no need for users to provide a complete node ordering. The system automatically determine the complete node ordering when users only can give a partial node ordering or even no prior at all. Experiment results show that our algorithm performs a little better than original K2 algorithm in the application to automatic semantic annotation for video shots
Sponsorship	IEEE ICIC Int. National Natural Sci. Found. of China Beijing Jiaotong Univ. Kaosiung Univ. of Appl. Sci
Starting Page	217
Ending Page	220
File Size	150134
Page Count	4
File Format	PDF
ISBN	0769526160
DOI	10.1109/ICICIC.2006.253
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bridges System performance Bayesian methods Humans Information technology Mutual information Videos
Content Type	Text
Resource Type	Article

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