Robust Orthogonal Particle Swarm Optimization for estimating the fundamental matrix

In this paper, we present a novel method which uses PSO combined LMedS and orthogonal array to improve the estimation of fundamental matrix. We first translate the fundamental matrix estimation problem into the PSO problem. Then, we use the orthogonal array and LMedS to make the initial particles for more robust. Our experiments show that the proposed ROPSO produces more accurate estimation of fundamental matrices than the traditional LMedS, and the ROPSO has higher probability to find the optimal solution than the LMedS.