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16th International Conference on Pattern Recognition (ICPR'02) - Volume 2
Extension of Hidden Markov Models to Deal with Multiple Candidates of Observations and its Application to Mobile-Robot-Oriented Gesture Recognition
Quebec City, QC, Canada
August 11-August 15
ISBN: 0-7695-1695-X
ASCII Text
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Yosuke Sato, Tetsunori Kobayashi, "Extension of Hidden Markov Models to Deal with Multiple Candidates of Observations and its Application to Mobile-Robot-Oriented Gesture Recognition," Pattern Recognition, International Conference on, vol. 2, pp. 20515, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 2, 2002.
 
 
BibTex
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@article{ 10.1109/ICPR.2002.1048351,
author = {Yosuke Sato and Tetsunori Kobayashi},
title = {Extension of Hidden Markov Models to Deal with Multiple Candidates of Observations and its Application to Mobile-Robot-Oriented Gesture Recognition},
journal ={Pattern Recognition, International Conference on},
volume = {2},
year = {2002},
issn = {1051-4651},
pages = {20515},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1048351},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - Extension of Hidden Markov Models to Deal with Multiple Candidates of Observations and its Application to Mobile-Robot-Oriented Gesture Recognition
SN - 1051-4651
SP
EP
A1 - Yosuke Sato,
A1 - Tetsunori Kobayashi,
PY - 2002
KW - null
VL - 2
JA - Pattern Recognition, International Conference on
ER -
 
Yosuke Sato, Waseda University
Tetsunori Kobayashi, Waseda University
We propose a modified Hidden Markov Model (HMM) with a view to improving gesture recognition in the moving camera condition. We define a new gesture recognition framework in which multiple candidates of feature vectors are generated with confidence measures and the HMM is extended to deal with these multiple feature vectors. Experimental analysis comparing the proposed system with feature vectors based on DCT and the method of selecting only one candidate feature point verify the effectiveness of the technique.
Citation:
Yosuke Sato, Tetsunori Kobayashi, "Extension of Hidden Markov Models to Deal with Multiple Candidates of Observations and its Application to Mobile-Robot-Oriented Gesture Recognition," icpr, vol. 2, pp.20515, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 2, 2002
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