A Versatile Method for Omnidirectional Stereo Camera Calibration Based on BP Algorithm

This study describes a full model of calibrating an omnidirectional stereo vision system, which includes the rotation and translation between the camera and mirrors, and an algorithm implemented with a backpropagation technique of the neural network to determine this relative position from observations of known points in a single image. The system is composed of a perspective camera and two hyperbolic mirrors, which are configured to be separate and coaxial besides sharing one focus that coincides with the camera center for providing a single projection point. We divide the calibration into two steps. The first step we calibrate the camera’s intrinsics without the mirrors in order to reduce computational complexity and in the second step we estimate the pose parameters of the CCD camera with respect to the mirrors based on a Levenberg-Marquart Backpropagation (LMBP) algorithm. The proposed tech- nique can be easily applied to all kinds of catadioptric sensors and various amounts of misalignment between the mirrors and cameras.