Dense 3D Reconstruction Based on Photometric Stereo with Unknown Light Source via Energy Minimization Framework

In this paper,an novel method would be suggested to achieve an dense 3D reconstruction of objects using photometric stereo without any prior knowledge of light source. Using the photometric images I which is constructed with its columns equal to number of photometric images captured and rows equal to number of pixels in a photometric image. A per pixel initial surface normal estimate is computed based upon SVD of the image matrix I. A effective regularization technique has been applied on the initial normal estimate within the energy minimization framework which via graph cuts to regularize them and preserve the underlying discontinuities better.Finally, the regularized surface normals are integrated to recover the surface of the object. The algorithm has been tested on synthetic as well as real datasets and very encouraging results have been obtained.