Face recognition based on fringe pattern analysis
Hong Mei Guo · Optical Engineering · 2010
Two-dimensional face-recognition techniques suffer from facial texture and illumination variations. Although 3-D techniques can overcome these limitations, the reconstruction and storage expenses of 3-D information are extremely high. We present a novel face-recognition method that directly utilizes 3-D information encoded in face fringe patterns without having to reconstruct 3-D geometry. In the proposed method, a digital video projector is employed to sequentially project three phase-shifted sinusoidal fringe patterns onto the subject's face. Meanwhile, a camera is used to capture the distorted fringe patterns from an offset angle. Afterward, the face fringe images are analyzed by the phase-shifting method and the Fourier transform method to obtain a spectral representation of the 3-D face. Finally, the eigenface algorithm is applied to the face-spectrum images to perform face recognition. Simulation and experimental results demonstrate that the proposed method achieved satisfactory recognition rates with reduced computational complexity and storage expenses.