TY - GEN
T1 - Personal identification by multiresolution analysis of lifting dyadic wavelets
AU - Takan, Shigeru
AU - Niijima, Koichi
AU - Kuzume, Koichi
N1 - Publisher Copyright:
© 2004 EUSIPCO.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2015/4/3
Y1 - 2015/4/3
N2 - This paper proposes a novel method for identifying persons by multiresolution analysis of lifting dyadic wavelets. Our method consists of three procedures: face learning, detection and identification. In the learning procedure, new highpass filters for capturing facial parts are constructed by tuning free parameters in the lifting scheme. By using the learned filters, human faces can be detected from each of video frames. A person whose face is detected in a maximum number of frames is identified as a target person. Experimental results show that our personal identification algorithm is fast and accurate.
AB - This paper proposes a novel method for identifying persons by multiresolution analysis of lifting dyadic wavelets. Our method consists of three procedures: face learning, detection and identification. In the learning procedure, new highpass filters for capturing facial parts are constructed by tuning free parameters in the lifting scheme. By using the learned filters, human faces can be detected from each of video frames. A person whose face is detected in a maximum number of frames is identified as a target person. Experimental results show that our personal identification algorithm is fast and accurate.
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M3 - Conference contribution
AN - SCOPUS:84979916796
T3 - European Signal Processing Conference
SP - 2283
EP - 2286
BT - 2004 12th European Signal Processing Conference, EUSIPCO 2004
PB - European Signal Processing Conference, EUSIPCO
T2 - 12th European Signal Processing Conference, EUSIPCO 2004
Y2 - 6 September 2004 through 10 September 2004
ER -