Facial shape-from-shading using features detection method
Lyes Abada, Saliha Aouat · International Journal of Advanced Intelligence Paradigms · 2016
The shape reconstruction from one image is an important problem in the computer vision field. It is the so-called shape from shading problem (SFS). It is known to be an ill-posed problem, because each pixel has a family (cone) of surface normal's satisfying the image-irradiance equation. To make the shape from shading problem well-posed, several constraints were imposed on the surface of the 3D object, the model of the camera, and the light source which illuminates the 3D object. The idea of the proposed method is to use a facial features detection method to determine the singular points of the face in order to use them to generate the 3D object. It occurs in two main steps: the first step is the extraction of the facial features (the eyes, the nose and the mouth). Using this information, we can extract the singular points which represent the maximum gray-scale value and apply the local fast-marching method to compute the depth of these points. The second step is the application of the global fast-marching to compute all points around the singular points. The proposed method is tested on real facial images.