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2005 IEEE International Conference on Multimedia and Expo
On the surplus value of semantic video analysis beyond the key frame
Amsterdam, Netherlands
July 06-July 06
ISBN: 0-7803-9331-7
ASCII Text
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C.G.M. Snoek, M. Worring, J.-M. Geusebroek, D. Koelma, F.J. Seinstra, "On the surplus value of semantic video analysis beyond the key frame," Multimedia and Expo, IEEE International Conference on, pp. 4 pp., 2005 IEEE International Conference on Multimedia and Expo, 2005.
 
 
BibTex
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@article{ 10.1109/ICME.2005.1521441,
author = {C.G.M. Snoek and M. Worring and J.-M. Geusebroek and D. Koelma and F.J. Seinstra},
title = {On the surplus value of semantic video analysis beyond the key frame},
journal ={Multimedia and Expo, IEEE International Conference on},
volume = {0},
year = {2005},
isbn = {0-7803-9331-7},
pages = {4 pp.},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICME.2005.1521441},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Multimedia and Expo, IEEE International Conference on
TI - On the surplus value of semantic video analysis beyond the key frame
SN - 0-7803-9331-7
SP
EP
A1 - C.G.M. Snoek,
A1 - M. Worring,
A1 - J.-M. Geusebroek,
A1 - D. Koelma,
A1 - F.J. Seinstra,
PY - 2005
KW - visual content
KW - semantic video analysis method
KW - video classification
KW - feature extraction
KW - key frame
KW - lexicon
KW - detection performance
VL - 0
JA - Multimedia and Expo, IEEE International Conference on
ER -
 
C.G.M. Snoek, Informatics Inst., Amsterdam Univ., Netherlands
M. Worring, Informatics Inst., Amsterdam Univ., Netherlands
J.-M. Geusebroek, Informatics Inst., Amsterdam Univ., Netherlands
D. Koelma, Informatics Inst., Amsterdam Univ., Netherlands
F.J. Seinstra, Informatics Inst., Amsterdam Univ., Netherlands
Typical semantic video analysis methods aim for classification of camera shots based on extracted features from a single keyframe only. In this paper, we sketch a video analysis scenario and evaluate the benefit of analysis beyond the key frame for semantic concept detection performance. We developed detectors for a lexicon of 26 concepts, and evaluated their performance on 120 hours of video data. Results show that, on average, detection performance can increase with almost 40% when the analysis method takes more visual content into account.
Index Terms:
visual content, semantic video analysis method, video classification, feature extraction, key frame, lexicon, detection performance
Citation:
C.G.M. Snoek, M. Worring, J.-M. Geusebroek, D. Koelma, F.J. Seinstra, "On the surplus value of semantic video analysis beyond the key frame," icme, pp.4 pp., 2005 IEEE International Conference on Multimedia and Expo, 2005
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