From Projective to Euclidean Reconstruction
Abstract
To make a Euclidean reconstruction of the world seen through a stereo rig, we can either use a calibration grid, and the results will rely on the precision of the grid and the extracted points of interest, or use self-calibration. Past work on self-calibration is focussed on the use of only one camera, and gives sometimes very unstable results. In this paper, we use a stereo rig which is supposed to be weakly calibrated using a method such as the one described in~\cite{deriche-zhang-etal:94}. Then, by matching two sets of points of the same scene reconstructed from different points of view, we try to find both the homography that maps the projective reconstruction~\cite{faugeras:92} to the Euclidean space and the displacement from the first set of points to the second set of points. We present results of the Euclidean reconstruction of a whole object from uncalibrated cameras using the method proposed here.