Title: Discriminative analysis of lip features for emotion recognition

Authors: Neeru Rathee; Dinesh Ganotra

Addresses: MSIT, Guru Gobind Singh Indraprastha University, Dwarka, New Delhi, India ' Indira Gandhi Delhi Technical University for Women, Formerly Indira Gandhi Institute of Technology Room No. 117-B, Applied Science and IT Block, Kashmere Gate, Delhi 110006, India

Abstract: There exist several emotion recognition techniques that use lip information in combination with other facial features. An attempt has been made in the presented work towards emotion recognition based only on lip features. Lip information is represented by extracting lip texture features and lip geometric features. Lip texture features are extracted using discrete cosine transformation while lip geometric features are extracted by modelling the lip shape using the localised active contour model. The extracted features are applied to support vector machine for emotion recognition. The proposed approach is evaluated on extended Cohn-Kanade and JAFFE database. It is evident from the experimental results that lip geometric features result in 85.76% recognition accuracy which is higher than the recognition accuracy using lip texture features 84.47%. In addition, combination of lip texture and geometric features results in 87.70% recognition accuracy, which is comparable to the state-of-the-art approaches.

Keywords: emotion recognition; facial expression recognition; active appearance model; support vector machine; SVM.

DOI: 10.1504/IJCVR.2017.087738

International Journal of Computational Vision and Robotics, 2017 Vol.7 No.6, pp.669 - 691

Received: 07 May 2015
Accepted: 08 Sep 2015

Published online: 24 Jul 2017 *

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