Personalised-face neutralisation using bestmatched face shape with a neutral-face database
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Author list: Petpairote C., Madarasmi S., Chamnongthai K.
Publisher: Wiley Open Access
Publication year: 2018
Journal: IET Computer Vision (1751-9632)
Volume number: 12
Issue number: 3
Start page: 252
End page: 260
Number of pages: 9
ISSN: 1751-9632
eISSN: 1751-9640
Languages: English-Great Britain (EN-GB)
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Abstract
Conventional personalised-face neutralisation methods use facial-expression databases; however, the database creation and maintenance is a tedious process, and should be minimised. Moreover, face-shape template should be also considerably used due to its crucial factor. This study proposes a personalised-face neutralisation method using best-matched face-shape template with neutral-face database. In personalised-face neutralisation, the best-matched face-shape template which is assumed as the most similar to the neutralisation expression face is found based on coarse-to-fine concept, and used for warping textures. Additionally, closed eyes are detected and opened up by using eye shape of the best-matched face shape, and mixed intensities of original closed-eye and the best-matched one. To evaluate the performance of the proposed method, experiments were performed using the CMU Multi-PIE database and the results reveal that the proposed method reduces gradient mean square error 0.07% on average and improves face recognition accuracy by 1.13% approximately comparing with the conventional method, while requiring only a single neutral database without expression images. ฉ The Institution of Engineering and Technology 2017.
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