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2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008)
Video Summarization Based on Semantic Feature Analysis and User Preference
June 11-June 13
ISBN: 978-0-7695-3158-8
ASCII Text
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Wen-Nung Lie, Kuo-Chiang Hsu, "Video Summarization Based on Semantic Feature Analysis and User Preference," Sensor Networks, Ubiquitous, and Trustworthy Computing, International Conference on, pp. 486-491, 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008), 2008.
 
 
BibTex
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@article{ 10.1109/SUTC.2008.88,
author = {Wen-Nung Lie and Kuo-Chiang Hsu},
title = {Video Summarization Based on Semantic Feature Analysis and User Preference},
journal ={Sensor Networks, Ubiquitous, and Trustworthy Computing, International Conference on},
volume = {0},
year = {2008},
isbn = {978-0-7695-3158-8},
pages = {486-491},
doi = {http://doi.ieeecomputersociety.org/10.1109/SUTC.2008.88},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Sensor Networks, Ubiquitous, and Trustworthy Computing, International Conference on
TI - Video Summarization Based on Semantic Feature Analysis and User Preference
SN - 978-0-7695-3158-8
SP486
EP491
A1 - Wen-Nung Lie,
A1 - Kuo-Chiang Hsu,
PY - 2008
VL - 0
JA - Sensor Networks, Ubiquitous, and Trustworthy Computing, International Conference on
ER -
 
A personalized video summarization system is proposed in this paper. "Personalized" means that each video can be summarized according to viewer's own preference. To meet user's preference, semantic features of each frame are detected so that their relevance to user preference can be determined. Users can be also capable of setting time or frame number constraint for video summary via a friendly interface. To summarize a video efficiently and effectively, a constrained optimization problem (subject to time constraint and video smoothness) is faced and solved to determine the non-uniform sampling rates for shots relevant to user preferences. Subjective tests show that the quality of the summarized video has a MOS of about 4.0, and the comprehension about the video contents is good.
Citation:
Wen-Nung Lie, Kuo-Chiang Hsu, "Video Summarization Based on Semantic Feature Analysis and User Preference," sutc, pp.486-491, 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008), 2008
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