From Projective to Euclidean Reconstruction

Frédéric Devernay 1 Olivier Faugeras 1
1 ROBOTVIS - Computer Vision and Robotics
CRISAM - Inria Sophia Antipolis - Méditerranée
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 Deriche et al. (1994). 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 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.
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Communication dans un congrès
CVPR - International Conference on Computer Vision and Pattern Recognition - 1996, 1996, San Francisco, United States. IEEE, pp.264 - 269, 1996, Computer Vision and Pattern Recognition, 1996. Proceedings. <10.1109/CVPR.1996.517084>
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Frédéric Devernay, Olivier Faugeras. From Projective to Euclidean Reconstruction. CVPR - International Conference on Computer Vision and Pattern Recognition - 1996, 1996, San Francisco, United States. IEEE, pp.264 - 269, 1996, Computer Vision and Pattern Recognition, 1996. Proceedings. <10.1109/CVPR.1996.517084>. <hal-00816706>

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