Using PSO metaheuristic to solve photometric 3D reconstruction

The photometric stereo is a basic domain in computer vision. It consists to reconstruct a 3D object using several intensity images taken by the same camera position and obtained under different lighting conditions. The photometric stereo allows to resolve the ambiguity of the Shape From Shading which reconstruct the 3D object using only one gray scale image and based on the same concepts of the image formation field. The Shape from Shading is considered as an ill-posed problem due to lack of information.In the literature we can find several works to solve the Photometry Stereo (PS). In this work we are interested to improve the 3D reconstruction by the mathematical solution "SVD decomposition" which is widely used and very known. We start our paper with an introduction, then we show the proposed method. we propose a new approach with several configurations to solving the Photometric Stereo (PS) using the Particle Swarm Optimization (PSO) meta-heuristic. We also propose an improvement using the integrability constraint on the 3D surface. Finally we show the obtained results and a comparison with a Singular Value Decomposition (SVD) method.