Spherical Spaces for Illumination Invariant Face Relighting
Amr Almaddah, Sadi Vural, Yasushi Mae,
Kenichi Ohara, and Tatsuo Arai
Department of Systems Innovation, Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama-cho, Toyonaka, Osaka 560-8531, Japan
In this paper, we propose a robust face relighting technique by using spherical space properties. The proposed method is done for reducing the illumination effects on face recognition. One single image is used as an input for recovering the face illumination and the recognition process. First, an internal training illumination database is generated by computing face albedo and face normal from 2D images under different lighting conditions. Based on the generated database, we analyze the target face pixels and compare them with the database by using pre-generated tiles. In this work, practical real time processing speed and small image size were considered when designing the framework. In contrast to other works, our technique requires no 3D face models for the training process and takes a single 2D image as an input. Experimental results on publicly available databases show that the proposed technique works well under severe illumination conditions and the method significantly improves the face recognition rates.
Kenichi Ohara, and Tatsuo Arai, “Spherical Spaces for Illumination Invariant Face Relighting,” J. Robot. Mechatron., Vol.25, No.5, pp. 840-847, 2013.
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