Stereo-based 3D Face Modeling using Annealing in Local Energy Minimization

In the past few years, 3D face modeling has gained significant attention. Reliable modeling of the face is necessary for good performance of a 3D assisted face recognition system. In this paper, we model 3D human face from binocular stereo images. The stereo matching problem has been formulated as an energy minimization problem that progressively propagates depth from reliable regions to unreliable regions by an annealing scheme. The concept of smooth 2D grid is used to enable regularizing the final depth solution. In the energy equation, area based matching is used for the data term. The smoothness term relies on annealing. The 2D grid facilitates the estimation of the smoothness parameter, from a correlation profile obtained from neighborhood of the grid node. It is evident from 3D modeling results that the proposed algorithm performs well on images of human faces.