Feasibility Study of Gabor Wavelet for Detection of Facial Expression: Facial Expression Recognition Based on Image Feature - Couverture souple

Kumbhar, Mahesh; Jadhav, Ashish; Walunjkar, Mahesh

 
9783659459733: Feasibility Study of Gabor Wavelet for Detection of Facial Expression: Facial Expression Recognition Based on Image Feature
Couverture souple
ISBN 10 : 3659459739 ISBN 13 : 9783659459733
Editeur : LAP LAMBERT Academic Publishing, 2013

Synopsis

This book summarizes the use of Gabor wavelet in the facial expression recognition system. The recognition of facial expressions implies finding solutions to three distinct types of problems. The first one relates to detection of faces in the image. Once the face location is known, the second problem is the detection of the salient features within the facial areas. The final analysis consists by using any classification model and the extracted facial features will identify the correct facial expression. Gabor filter are used to extract the different features. The unique features for four classes (Ex. Happy, Sad, Surprise and Disgust) will be kept as a reference to the new input image. The new image features will apply to feed-forward neural networks (classifier) for recognition of four different facial expressions. In this study the Japanese Female Facial Expression (JAFFE) database used which contains expressers that expressed expressions.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

This book summarizes the use of Gabor wavelet in the facial expression recognition system. The recognition of facial expressions implies finding solutions to three distinct types of problems. The first one relates to detection of faces in the image. Once the face location is known, the second problem is the detection of the salient features within the facial areas. The final analysis consists by using any classification model and the extracted facial features will identify the correct facial expression. Gabor filter are used to extract the different features. The unique features for four classes (Ex. Happy, Sad, Surprise and Disgust) will be kept as a reference to the new input image. The new image features will apply to feed-forward neural networks (classifier) for recognition of four different facial expressions. In this study the Japanese Female Facial Expression (JAFFE) database used which contains expressers that expressed expressions.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2013
Langue
anglais
ISBN 10 
3659459739
ISBN 13 
9783659459733
Reliure
Broché
Nombre de pages
88
Coordonnées du fabricant
non disponible
Personne responsable
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