In this thesis, we integrate existing methods and propose an automatic 3-D scene model reconstruction system. First, we estimate the camera poses using heirarchical appearance-based registration which is a pairwise registration method. Then,we detect repeated scenes in the RGB-D images with Scattering Transform and estimate camera translations and rotations using SURF, Arun, and RANSAC. The registration network is represented as a graph. Each node of the graph represent a RGB-D image and the camera pose. Each edge of the graph represent a pairwise registration result of two nodes. We hide the accumulated registration error using Lie-algebraic averaging. Experimental results show that the proposed method is comparable to the existing state-of-the-art methods.