Curve-Based Stereo: Figural Continuity and Curvature
Abstract
An edge-based trinocular stereovision algorithm is presented. The primitives it works on are cubic B-spline approximations of the 2-D edges. This allows one to deal conveniently with curvature and to extend to some nonpolyhedral scenes to previous stereo algorithms. To build a matching primitive, the principle of the algorithm is, first, to find a triplet of corresponding points on three splines. This is provided by the bootstrapping part. Second, the algorithm propagates along the three supporting splines to find other matching points. This provides a set of ordered point triplets along these three splines, for which all the matching constraints are verified. This primitive constitutes a trinocular hypothesis. The set of all hypotheses is obtained by propagating from all the point triplets provided by the bootstrapping process. A criterion based on the size of the hypotheses is then used to choose among them a compatible set with respect to the uniqueness constraint. Results of several 3-D reconstructed scenes are shown.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Robert and Faugeras. "Curve-Based Stereo: Figural Continuity and Curvature." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1991. doi:10.1109/CVPR.1991.139661Markdown
[Robert and Faugeras. "Curve-Based Stereo: Figural Continuity and Curvature." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1991.](https://mlanthology.org/cvpr/1991/robert1991cvpr-curve/) doi:10.1109/CVPR.1991.139661BibTeX
@inproceedings{robert1991cvpr-curve,
title = {{Curve-Based Stereo: Figural Continuity and Curvature}},
author = {Robert, Luc and Faugeras, Olivier D.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1991},
pages = {57-62},
doi = {10.1109/CVPR.1991.139661},
url = {https://mlanthology.org/cvpr/1991/robert1991cvpr-curve/}
}