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Facial Expression Recognition Using an Improved Embedded HMM |
ZHENG Fang-Ying1,2, ZHAO Jie-Yu1 |
1.Research Institute of Computer Science and Technology, Ningbo University, Ningbo 3152112. Network Center, Ningbo University, Ningbo 315211 |
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Abstract An embedded hidden markov model (e-HMM) based approach for facial expression recognition is proposed. It makes use of an optimized set of observation vectors obtained from the 2D-DCT coefficients of the facial region of interest. The e-HMM is trained with segmental K-means algorithm and used for the facial expression recognition. The experimental results show the remarkable improvement of the performance and robustness of the facial expression recognition system.
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Received: 28 May 2007
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