A Study on Appearance-Based Facial Expression Recognition Using Active Shape Model


KIPS Transactions on Software and Data Engineering, Vol. 5, No. 1, pp. 43-50, Jan. 2016
10.3745/KTSDE.2016.5.1.43, Full Text:

Abstract

This paper introduces an appearance-based facial expression recognition method using ASM landmarks which is used to acquire a detailed face region. In particular, EHMM-based algorithm and SVM classifier with histogram feature are employed to appearance-based facial expression recognition, and performance evaluation of proposed method was performed with CK and JAFFE facial expression database. In addition, performance comparison was achieved through comparison with distance-based face normalization method and a geometric feature-based facial expression approach which employed geometrical features of ASM landmarks and SVM algorithm. As a result, the proposed method using ASM-based face normalization showed performance improvements of 6.39% and 7.98% compared to previous distance-based face normalization method for CK database and JAFFE database, respectively. Also, the proposed method showed higher performance compared to geometric feature-based facial expression approach, and we confirmed an effectiveness of proposed method.


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Cite this article
[IEEE Style]
D. J. Kim and J. H. Shin, "A Study on Appearance-Based Facial Expression Recognition Using Active Shape Model," KIPS Transactions on Software and Data Engineering, vol. 5, no. 1, pp. 43-50, 2016. DOI: 10.3745/KTSDE.2016.5.1.43.

[ACM Style]
Dong Ju Kim and Jeong Hoon Shin. 2016. A Study on Appearance-Based Facial Expression Recognition Using Active Shape Model. KIPS Transactions on Software and Data Engineering, 5, 1, (2016), 43-50. DOI: 10.3745/KTSDE.2016.5.1.43.