Motion Adjustment for Extrinsic Calibration of Cameras with Non-overlapping Views

Abstract

This paper adresses the issue of calibrating multiple cameras on a mobile platform. Due to decreasing sensor prices and increasing processing performance, the use of multiple cameras in vehicles becomes an attractive possibility for environment perception. To avoid restrictions relating to the camera arrangement, we focus on non-overlapping camera configurations. Hence, we resign the usage of corresponding features between the cameras. The hand-eye calibration technique based on visual odometry is basically able to solve this problem by exploiting the cameras' motions. However, this technique suffers from inaccuracies in motion estimation. Especially the absolute magnitudes of the translational velocities of each camera are essential for a successful calibration. This contribution presents a novel approach to solve the hand eye calibration problem for two cameras on a mobile platform with non-overlapping fields of view. The so-called motion adjustment simultaneously estimates the extrinsic parameters up to scale as well as the reltive motion magnitudes. Results with simulated and real data are presented.