Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2116
Title: Robust Facial Expression Recognition using Gabor Feature and Bayesian Discriminating Classifier
Authors: Piparsaniyan, Yamini
Sharma, V K
Mahapatra, K K
Keywords: Bayesian classification
Computer vision
Emotion recognition
Gabor features
PCA
Issue Date: Apr-2014
Citation: IEEE International Conference on Communicatoin & SIgnal Processing ICCSP 2014, 3rd-5th April 2014, Adhiparashakti Engineering College, Melmaruvathur, Tamilnadu.
Abstract: Automatic facial expression recognition is important for effective Human computer interaction (HCI) as well as autistic children for communication. In this paper, we propose emotion recognition using Gabor feature and simple Bayesian discriminating classifier based on principal component analysis (PCA) for emotion recognition. The multi class classification strategic has been applied based on highest value of log likelihood after training different emotions class. Facial expression images from JAFFE database have been used for training as well as testing. Very high accuracy (96.73 %) of emotion recognition has been obtained with proposed method
Description: Copyright belongs to the Proceeding of Publisher
URI: http://hdl.handle.net/2080/2116
Appears in Collections:Conference Papers

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