The impact of specular highlights on 3D-2D face recognition
Vincent Christlein, Christian Rieß, Elli Angelopoulou, Georgios Evangelopoulos, Ioannis A. Kakadiaris · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
One of the most popular form of biometrics is face recognition. Face recognition techniques typically assume that a face exhibits Lambertian reectance. However, a face often exhibits prominent specularities, especially in outdoor environments. These specular highlights can compromise an identity authentication. In this work, we analyze the impact of such highlights on a 3D-2D face recognition system. First, we investigate three different specularity removal methods as preprocessing steps for face recognition. Then, we explicitly model facial specularities within the face detection system with the Cook-Torrance reflectance model. In our experiments, specularity removal increases the recognition rate on an outdoor face database by about 5% at a false alarm rate of 10-3. The integration of the Cook-Torrance model further improves these results, increasing the verification rate by 19% at a FAR of 10-3.