3D face modeling based on structured-light assisted stereo sensor

In this paper we present a 3D human face reconstruction framework based on stereo sensor coupled with a structured lighting source. Starting from two calibrated images, the active part (video projector) which project controlled lights, allows the operator to locate two sets of structured features with sub-pixel accuracy in both left and right images. Then, exploiting epipolar geometry improves the matching process by reducing its complexity from a bidirectional to a unidirectional search problem. Finally, we perform an adapted dynamic programming algorithm to obtain corresponding features in each conjugated scanline separately. Final three dimensional face models are achieved by a pipeline of four steps: (a) stereo triangulation, (b) data interpolation based on cubic spline models, (c) Delaunay triangulation-based meshing, and (d) texture mapping process.