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Anchorage, AK, USA
June 23, 2008 to June 28, 2008
ISBN: 978-1-4244-2339-2
pp: 1-8
Anan Liu , Virtual Reality Laboratory, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China
Sheng Tang , Virtual Reality Laboratory, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China
Yongdong Zhang , Virtual Reality Laboratory, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China
Yan Song , Virtual Reality Laboratory, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China
Jintao Li , Virtual Reality Laboratory, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China
Zhaoxuan Yang , Department of Electronic Engineering, Tianjin University, 300072, China
ABSTRACT
In this paper, we specially propose a hierarchical framework for movie content analysis. The purpose of our work is trying to realize computers’ understanding for movie content, especially “Who, What, Where, How” which occur in the storyline by imitating human perception and cognition. The framework consists of two hierarchies. As for the low level part, we originally construct the human attention model with temporal information motivated by the Weber-Fechner Law to depict the variation of human perception in multiple modalities. As for the high level part, we focus on semantic understanding of different granularities of videos and simulate human cognition for movie content. Based on this hierarchical framework, we present its applications on semantic retrieval, video summarization and content filter. The promising results of users’ subjective assessment indicate that the proposed framework is applicable for automatic analysis of movie content by computers.
CITATION
Anan Liu, Sheng Tang, Yongdong Zhang, Yan Song, Jintao Li, Zhaoxuan Yang, "A hierarchical framework for movie content analysis: Let computers watch films like humans", CVPRW, 2008, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops 2008, pp. 1-8, doi:10.1109/CVPRW.2008.4563040
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