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http://dx.doi.org/10.3745/KTSDE.2014.3.3.135

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

Kim, Dong-Ju (대구경북과학기술원 IT융합연구부)
Lee, Sang-Heon (대구경북과학기술원 IT융합연구부)
Sohn, Myoung-Kyu (대구경북과학기술원 IT융합연구부)
Publication Information
KIPS Transactions on Software and Data Engineering / v.3, no.3, 2014 , pp. 135-138 More about this Journal
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.
Keywords
Facial Expression Recognition; Overfitting; Hidden Markov Model;
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Times Cited By KSCI : 1  (Citation Analysis)
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