A generic framework of user attention model and its application in video summarization

Due to the information redundancy of video, automatically extracting essential video content is one of key techniques for accessing and managing large video library. In this paper, we present a generic framework of a user attention model, which estimates the attentions viewers may pay to video conte...

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Bibliographic Details
Published in:IEEE transactions on multimedia 2005-10, Vol.7 (5), p.907-919
Main Authors: MA, Yu-Fei, HUA, Xian-Sheng, LIE LU, ZHANG, Hong-Jiang
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Asia
Attention modeling
Computer science
control theory
systems
Content management
Data mining
Electronics
Exact sciences and technology
Filtering
Human
Humans
Indexing
Information filtering
Information filters
Libraries
Mathematical models
Multimedia
Pattern recognition. Digital image processing. Computational geometry
Recording and replay of audio and video signals
Robustness
Semantics
Storage and reproduction of information
Studies
Technology management
video content analysis
video summarization
Visual
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Summary:Due to the information redundancy of video, automatically extracting essential video content is one of key techniques for accessing and managing large video library. In this paper, we present a generic framework of a user attention model, which estimates the attentions viewers may pay to video contents. As human attention is an effective and efficient mechanism for information prioritizing and filtering, user attention model provides an effective approach to video indexing based on importance ranking. In particular, we define viewer attention through multiple sensory perceptions, i.e. visual and aural stimulus as well as partly semantic understanding. Also, a set of modeling methods for visual and aural attentions are proposed. As one of important applications of user attention model, a feasible solution of video summarization, without fully semantic understanding of video content as well as complex heuristic rules, is implemented to demonstrate the effectiveness, robustness, and generality of the user attention model. The promising results from the user study on video summarization indicate that the user attention model is an alternative way to video understanding.
ISSN:1520-9210
1941-0077
DOI:10.1109/TMM.2005.854410