Paper
31 May 2013 The impact of specular highlights on 3D-2D face recognition
Vincent Christlein, Christian Riess, Elli Angelopoulou, Georgios Evangelopoulos, Ioannis Kakadiaris
Author Affiliations +
Abstract
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.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vincent Christlein, Christian Riess, Elli Angelopoulou, Georgios Evangelopoulos, and Ioannis Kakadiaris "The impact of specular highlights on 3D-2D face recognition", Proc. SPIE 8712, Biometric and Surveillance Technology for Human and Activity Identification X, 87120T (31 May 2013); https://doi.org/10.1117/12.2019014
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Facial recognition systems

3D modeling

Bidirectional reflectance transmission function

Databases

Detection and tracking algorithms

Nose

Skin

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