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On Mugshot-based Arbitrary View Face Recognition
Conference proceeding

On Mugshot-based Arbitrary View Face Recognition

Jie Liang, Feng Liu, Huan Tu, Qijun Zhao and Anil K. Jain
2018 24th International Conference on Pattern Recognition (ICPR), v 2018-, pp 3126-3131
Aug 2018
DOI: https://doi.org/10.1109/ICPR.2018.8546094

Abstract

Face Face recognition Image reconstruction Probes Shape Three-dimensional displays Two dimensional displays
Despite the wide usage of mugshot images in forensic applications, they are underutilized in existing automated face recognition systems. In this paper, we propose a novel mugshot-based arbitrary view face recognition method. Our approach reconstructs full 3D faces via cascaded regression in shape space with efficient seamless texture recovery. Unlike existing methods, it makes full use of the frontal and profile views available in mugshot images, and thus generates accurate and realistic 3D faces. Multi-view face images are synthesized from the reconstructed 3D faces to enlarge the gallery so that arbitrary view faces can be better recognized. Evaluation experiments were conducted on BFM and Multi-PIE databases by using state-of-the-art deep learning (DL) based face matchers. The results demonstrate the effectiveness of our proposed method and show that DL-based face matchers can benefit from mugshot images and the reconstructed 3D faces, especially for recognizing large off-angle faces.

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3 Record Views
7 citations in Web of Science
6 citations in Scopus

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Computer Science, Artificial Intelligence
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