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3D Facial expression recognition based on basic geometric features

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3 Author(s)
Xiaoli Li ; Instn. of Inf. Sci., Beijing Jiaotong Univ., Beijing, China ; Qiuqi Ruan ; Yue Ming

This paper describes a 3D facial expression recognition approach based on distance and angle features, which can be got from the localized facial feature points. The probabilistic Neutral Network (PNN) architecture is used to classify the facial expressions based on BU-3DFE database. This paper adds the facial feature vectors with the information of slopes and the angles as the feature vectors got from the facial feature points, not only the distance information mentioned in the previous work. Thus it receives a better performance with an average recognition rate of 90.2%.

Published in:

Signal Processing (ICSP), 2010 IEEE 10th International Conference on

Date of Conference:

24-28 Oct. 2010

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