Dynamic facial expression recognition based on geometric and texture features

Ming Li; Zengfu Wang

doi:10.1117/12.2302933

10 April 2018 Dynamic facial expression recognition based on geometric and texture features

Ming Li, Zengfu Wang

Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 106150T (2018) https://doi.org/10.1117/12.2302933
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China

Abstract

Recently, dynamic facial expression recognition in videos has attracted growing attention. In this paper, we propose a novel dynamic facial expression recognition method by using geometric and texture features. In our system, the facial landmark movements and texture variations upon pairwise images are used to perform the dynamic facial expression recognition tasks. For one facial expression sequence, pairwise images are created between the first frame and each of its subsequent frames. Integration of both geometric and texture features further enhances the representation of the facial expressions. Finally, Support Vector Machine is used for facial expression recognition. Experiments conducted on the extended Cohn-Kanade database show that our proposed method can achieve a competitive performance with other methods.

Citation Download Citation

Ming Li and Zengfu Wang "Dynamic facial expression recognition based on geometric and texture features", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106150T (10 April 2018); https://doi.org/10.1117/12.2302933

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