Accurate feature detection and matching for the tracking of calibration parameters in multi-camera acquisition systems
The 3D reconstruction's quality of multiple-camera acquisition systems is strongly influenced by the accuracy of the camera calibration procedure. The acquisition of long sequences is, in fact, very sensitive to mechanical shocks, vibrations and thermal changes on cameras and supports, as they could result in a significant drift of the camera parameters. In this paper we propose a technique which is able to keep track of the camera parameters and, whenever possible, to correct them accordingly. This technique does not need any a-priori knowledge or test objects to be placed in the scene, but exploits features that are already present in the scene itself. In fact it performs an accurate detection, matching and back-projection of luminance corners and spots in the scene space. Experimental results on real sequences are reported in order to prove the ability of the proposed technique to detect a change in the calibration and to re-calibrate the camera setup with an accuracy that depends on the number of available feature points.