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000100006 024 8_ $9 driver $9 artpubuab $a oai:ddd.uab.cat:100006
000100006 035 __ $9 articleid $a 15775097v11n1p41
000100006 041 __ $a eng
000100006 100 __ $a Huang, Hung-Fu $u National Cheng Kung University (Taiwan). Department of Electrical Engineering
000100006 245 1_ $a Facial Expression Recognition Using New Feature Extraction Algorithm
000100006 520 3_ $a This paper proposes a method for facial expression recognition. Facial feature vectors are generated from keypoint descriptors using Speeded-Up Robust Features. Each facial feature vector is then normalized and next the probability density function descriptor is generated. The distance between two probability density function descriptors is calculated using Kullback Leibler divergence. Mathematical equation is employed to select certain practicable probability density function descriptors for each grid, which are used as the initial classification. Subsequently, the corresponding weight of the class for each grid is determined using a weighted majority voting classifier. The class with the largest weight is output as the recognition result. The proposed method shows excellent performance when applied to the Japanese Female Facial Expression database.
000100006 546 __ $a Anglès
000100006 540 __ $a Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. $u http://creativecommons.org/licenses/by-nc-nd/3.0/es/
000100006 599 __ $a recerca
000100006 653 1_ $a Speeded-Up Robust Features
000100006 653 1_ $a Probability density function
000100006 653 1_ $a Kullback Leibler
000100006 653 1_ $a Divergence
000100006 653 1_ $a Weighted majority voting
000100006 655 _4 $a info:eu-repo/semantics/article
000100006 655 _4 $a info:eu-repo/semantics/publishedVersion
000100006 700 __ $a Tai, Shen-Chuan $u National Cheng Kung University (Taiwan). Department of Electrical Engineering
000100006 773 __ $g Vol. 11, Núm. 1 (2012), p. 41-54 $t ELCVIA : Electronic Letters on Computer Vision and Image Analysis $x 1577-5097
000100006 856 40 $p 14 $s 335004 $u http://ddd.uab.cat/pub/elcvia/elcvia_a2012v11n1/elcvia_a2012v11n1p41.pdf
000100006 973 __ $f 0041 $l 54 $m  $n 1 $v 11 $x elcvia_a2012v11n1 $y 2012
000100006 980 __ $a ARTPUB $b UAB $b ELCVIA