This paper is concerned with the acquisition of model data for automatic 3D face recognition applications. As 3D methods become progressively more popular in face recognition research, the need for fast and accurate data capture has become crucial. This paper is motivated by this need and offers three primary contributions. Firstly, the paper demonstrates that four-source photometric stereo offers a potential means for data capture that is computationally and financially viable and easily deployable in commercial settings. We have shown that both visible light and less intrusive near infrared light is suitable for facial illumination. The second contribution is a detailed set of experimental results that compare the accuracy of the device to ground truth, which was captured using a commercial projected pattern range finder. Importantly, we show that not only is near infrared light a valid alternative to the more commonly exploited visible light, but that it actually gives more accurate reconstructions. Finally, we assess the validity of the Lambertian assumption on skin reflectance data and show that better results may be obtained by incorporating more advanced reflectance functions, such as the Oren-Nayar model.
展开▼
