Feature Extraction Method of 2D-DCT for Facial Expression Recognition


KIPS Transactions on Software and Data Engineering, Vol. 3, No. 3, pp. 135-140, Mar. 2014
10.3745/KTSDE.2014.3.3.135,   PDF Download:

Abstract

This paper devices a facial expression recognition method robust to overfitting using 2D-DCT and EHMM algorithm. In particular, this paper achieves enhanced recognition performance by setting up a large window size for 2D-DCT feature extraction and extracting the observation vectors of EHMM. The experimental results on the CK facial expression database and the JAFFE facial expression database showed that the facial expression recognition accuracy was improved according as window size is large. Also, the proposed method revealed the recognition accuracy of 87.79% and showed enhanced recognition performance ranging from 46.01% to 50.05% in comparison to previous approaches based on histogram feature, when CK database is employed for training and JAFFE database is used to test the recognition accuracy.


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Cite this article
[IEEE Style]
D. J. Kim, S. H. Lee and M. K. Sohn, "Feature Extraction Method of 2D-DCT for Facial Expression Recognition," KIPS Transactions on Software and Data Engineering, vol. 3, no. 3, pp. 135-140, 2014. DOI: 10.3745/KTSDE.2014.3.3.135.

[ACM Style]
Dong Ju Kim, Sang Heon Lee, and Myoung Kyu Sohn. 2014. Feature Extraction Method of 2D-DCT for Facial Expression Recognition. KIPS Transactions on Software and Data Engineering, 3, 3, (2014), 135-140. DOI: 10.3745/KTSDE.2014.3.3.135.