3D Object Reconstruction from Uncalibrated Images using an Off-the-Shelf Camera

Three-dimensional (3D) objects reconstruction using just bidimensional (2D) images has been a major research topic in Computer Vision. However, it is still a hard problem to address, when automation, speed and precision are required and/or the objects have complex shapes or image properties. In this paper, we compare two Active Computer Vision methods frequently used for the 3D reconstruction of objects from image sequences, acquired with a single off-the-shelf CCD camera: Structure From Motion (SFM) and Generalized Voxel Coloring (GVC). SFM recovers the 3D shape of an object based on the relative motion involved, while VC is a volumetric method that uses photo-consistency measures to build the required 3D model. Both methods considered do not impose any kind of restrictions on the relative motion involved.