Abstract
This paper presents a real-time facial expression recognition system based on geometric features. The geometric feature extraction is based on a hybrid method. This method first uses ASM to track the fiducial points coarsely and then applies a method based on threshold segmentation and deformable model to correct the mouth fiducial points due to the incorrect locations in the presence of non-linear image variations such as those caused by large facial expression changes. The geometric features extracted from the fiducial points are classified in one of the seven basic expressions by SVM classifier. The experiment shows the recognition speed can achieve about 12 fps.
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Zhou, Q., Wang, X. (2013). Real-Time Facial Expression Recognition System Based-On Geometric Features. In: Lu, W., Cai, G., Liu, W., Xing, W. (eds) Proceedings of the 2012 International Conference on Information Technology and Software Engineering. Lecture Notes in Electrical Engineering, vol 212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34531-9_47
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DOI: https://doi.org/10.1007/978-3-642-34531-9_47
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