Three-dimensional facial digitization using advanced digital image correlation

Presented in this paper is an effective technique to acquire the three-dimensional (3D) digital images of the human face without the use of active lighting and artificial patterns. The technique is based on binocular stereo imaging and digital image correlation, and it includes two key steps: camera calibration and image matching. The camera calibration involves a pinhole model and a bundle-adjustment approach, and the governing equations of the 3D digitization process are described. For reliable pixel-to-pixel image matching, the skin pores and freckles or lentigines on the human face serve as the required pattern features to facilitate the process. It employs feature-matching-based initial guess, multiple subsets, iterative optimization algorithm, and reliability-guided computation path to achieve fast and accurate image matching. Experiments have been conducted to demonstrate the validity of the proposed technique. The simplicity of the approach and the affordable cost of the implementation show its practicability in scientific and engineering applications. (c) 2018 Optical Society of America