Structure From Motion Using Sequential Monte Carlo Methods

Gang Qian, Rama Chellappa

Abstract: In this paper the structure from motion (SfM) problem is addressed using sequential Monte Carlo methods. A new SfM algorithm based on random sampling is derived to estimate the posterior distributions of camera camera motion and scene structure for the perspective projection camera model. Experimental results show that challenging issues in solving the structure from motion problem including errors in feature tracking, feature occlusion, motion/structure ambiguity, processing mixed-domain sequences and handling mismatched features can be well modeled and effectively addressed using the proposed method.