Improved foundamental matrix computation and optimization method in parallel calibration of multi-camera system

Abstract

Multi-camera system has a number of cameras and complex space distribution,hence the calibration in multicamera system is inefficient.The calculation of fundamental matrix and nonlinear optimization are the key steps in camera calibration algorithm.In the light of independent marked points in multi-camera system calibration,fundamental matrix based on RANdom SAmple Consensus(RANSAC) and increment equation in nonlinear optimization were improved,and a parallel calibration algorithm for multi-camera system was proposed.Based on the analysis of the parallel process of calibration,this algorithm improved the efficiency of the calibration time.Compared with the traditional camera calibration algorithm,it makes the time complexity of calibration reduce from O(n3) to O(n).The experiments show that the parallel algorithm reduces the time obviously without any loss in precision,thus realizing fast multi-camera system calibration.