1 February 2018 System for face recognition under expression variations of neutral-sampled individuals using recognized expression warping and a virtual expression-face database
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Abstract
The practical identification of individuals using facial recognition techniques requires the matching of faces with specific expressions to faces from a neutral face database. A method for facial recognition under varied expressions against neutral face samples of individuals via recognition of expression warping and the use of a virtual expression-face database is proposed. In this method, facial expressions are recognized and the input expression faces are classified into facial expression groups. To aid facial recognition, the virtual expression-face database is sorted into average facial-expression shapes and by coarse- and fine-featured facial textures. Wrinkle information is also employed in classification by using a process of masking to adjust input faces to match the expression-face database. We evaluate the performance of the proposed method using the CMU multi-PIE, Cohn–Kanade, and AR expression-face databases, and we find that it provides significantly improved results in terms of face recognition accuracy compared to conventional methods and is acceptable for facial recognition under expression variation.
© 2018 SPIE and IS&T
Chayanut Petpairote, Chayanut Petpairote, Suthep Madarasmi, Suthep Madarasmi, Kosin Chamnongthai, Kosin Chamnongthai, } "System for face recognition under expression variations of neutral-sampled individuals using recognized expression warping and a virtual expression-face database," Journal of Electronic Imaging 27(1), 013014 (1 February 2018). https://doi.org/10.1117/1.JEI.27.1.013014 . Submission: Received: 17 September 2017; Accepted: 3 January 2018
Received: 17 September 2017; Accepted: 3 January 2018; Published: 1 February 2018
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