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Proceedings Paper

No-reference face image assessment based on deep features
Author(s): Guirong Liu; Yi Xu; Jinpeng Lan
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Paper Abstract

Face quality assessment is important to improve the performance of face recognition system. For instance, it is required to select images of good quality to improve recognition rate for the person of interest. Current methods mostly depend on traditional image assessment, which use prior knowledge of human vision system. As a result, the quality score of face images shows consistency with human vision perception but deviates from the processing procedure of a real face recognition system. It is the fact that the state-of-art face recognition systems are all built on deep neural networks. Naturally, it is expected to propose an efficient quality scoring method of face images, which should show high consistency with the recognition rate of face images from current face recognition systems. This paper proposes a non-reference face image assessment algorithm based on the deep features, which is capable of predicting the recognition rate of face images. The proposed face image assessment algorithm provides a promising tool to filter out the good input images for the real face recognition system to achieve high recognition rate.

Paper Details

Date Published: 28 September 2016
PDF: 7 pages
Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99711S (28 September 2016); doi: 10.1117/12.2239019
Show Author Affiliations
Guirong Liu, Shanghai Jiao Tong Univ. (China)
Yi Xu, Shanghai Jiao Tong Univ. (China)
Jinpeng Lan, Shanghai Jiao Tong Univ. (China)

Published in SPIE Proceedings Vol. 9971:
Applications of Digital Image Processing XXXIX
Andrew G. Tescher, Editor(s)

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