Title: An approach for facial expression classification

Authors: Ali Muhamed Ali; Hanqi Zhuang; Ali K. Ibrahim

Addresses: Department Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA ' Department Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA ' Department Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA

Abstract: In this paper, a new method for facial expression classification is proposed, which uses the histograms of oriented gradients (HOG) algorithm to extract facial expression features and the sparse representation classifier (SRC) to classify facial expressions with a large variation of poses. The HOG algorithm was selected due to its effectiveness in picking up both local and global facial expression features in different orientations and scales, and the SRC was chosen because of its proven effectiveness in face recognition. A novelty of the proposed approach is that given a facial image for classification, its pose is determined first to select a pose-dependent dictionary for the SRC procedure. The paper also discusses ways of selecting parameters for improving the effectiveness of the HOG algorithm. The proposed method was applied to two multi-pose facial expression databases and satisfactory results were obtained for the majority of facial expressions under various poses.

Keywords: facial expression; expression classification; histograms of oriented gradients; HOG; emotion detection; sparse representation classifier; SRC.

DOI: 10.1504/IJBM.2017.085665

International Journal of Biometrics, 2017 Vol.9 No.2, pp.96 - 112

Available online: 24 Jul 2017 *

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