Calibration of a stereo-vision system by the non-linear optimization of the motion of a calibration object
Abstract
A common and high-performance practice when carrying out euclidian reconstruc- tion from two cameras is to first calibrate both cameras thanks to a pair of images of a calibration object. However, it remains difficult to accurately determine the intrinsic parameters of each camera and we know their value have a significant effect on Euclidian reconstruction. Moreover, the calibration issued from a single pair of images of the calibration object do not exploit the device to the full. Indeed, measures used to perform the calibration may arbitrarily grow by the use of several pairs of images of the calibration object.It is the purpose of this paper to provide a method allowing to take advantage of such measures in order to improve simultaneously the accuracy of the intrinsic parameters and those of the ultimate Euclidian reconstruction. The method is based on a statistical and non-linear estimation of the parameters of the stereo rig.