Human expression recognition using facial shape based Fourier descriptors fusion

Ali Raza Shahid; Shehryar Khan; Hong Yan

doi:10.1117/12.2557450

31 January 2020 Human expression recognition using facial shape based Fourier descriptors fusion

Ali Raza Shahid, Shehryar Khan, Hong Yan

Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114330P (2020) https://doi.org/10.1117/12.2557450
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands

Abstract

Dynamic facial expression recognition has many useful applications in social networks, multimedia content analysis, security systems and others. This challenging process must be done under recurrent problems of image illumination and low resolution which changes at partial occlusions. This paper aims to produce a new facial expression recognition method based on the changes in the facial muscles. The geometric features are used to specify the facial regions i.e., mouth, eyes, and nose. The generic Fourier shape descriptor in conjunction with elliptic Fourier shape descriptor is used as an attribute to represent different emotions under frequency spectrum features. Afterwards a multi-class support vector machine is applied for classification of seven human expression. The statistical analysis showed our approach obtained overall competent recognition using 5-fold cross validation with high accuracy on well-known facial expression dataset.

Citation Download Citation

Ali Raza Shahid, Shehryar Khan, and Hong Yan "Human expression recognition using facial shape based Fourier descriptors fusion", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114330P (31 January 2020); https://doi.org/10.1117/12.2557450

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