Title: Facial expression recognition based on eigenspaces and principle component analysis

Authors: Ashim Saha; Sambhu Nath Pradhan

Addresses: Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, 799046, India ' Department of Electronics and Communication Engineering, National Institute of Technology Agartala, Tripura, 799046, India

Abstract: Facial expression detection or emotion recognition is one of the rising fields of research on intelligent systems. Emotion plays a significant role in non-verbal communication. An efficient face and facial feature detection algorithms plays as important role in indentifying of an emotion of a person at a particular moment. In this work, the authors implemented a system that recognises a person's facial expressions from the input images, using the algorithm of eigenspaces and principle component analysis (PCA). Eigenspaces are the face images which are projected onto a feature space that encodes the variation among known face images. PCA is used in this paper to make dimensional reduction of images in order to obtain a reduced representation of face images. The implementation is applied on three different facial expressions databases, extended Cohn-Kanade facial expression database, Japanese female facial expression database and self-made database in order to find out the effectiveness of the proposed method.

Keywords: facial expression; eigenspaces; principle component analysis; PCA; emotion detection; image processing.

DOI: 10.1504/IJCVR.2018.091980

International Journal of Computational Vision and Robotics, 2018 Vol.8 No.2, pp.190 - 200

Received: 04 Aug 2015
Accepted: 16 Mar 2016
Published online: 24 May 2018 *

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