Matching of 3D Curves Using Semi-Differential Invariants
Abstract
A method for matching 3-D curves under Euclidean motions is presented. Our approach uses a semi-differential invariant description requiring only first derivatives and one reference point, thus avoiding the computation of high order derivatives. A novel curve similarity measure building on the notion of /spl epsiv/-reciprocal correspondence is proposed. It is shown that by combining /spl epsiv/-reciprocal correspondence with the robust least median of squares motion estimation, the registration of partially occluded curves can be accomplished. An experiment with real curves extracted from 3-D surfaces demonstrates that curve matching can be successfully performed even on data from a simple and cheap 3-D sensor.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Pajdla and Van Gool. "Matching of 3D Curves Using Semi-Differential Invariants." IEEE/CVF International Conference on Computer Vision, 1995. doi:10.1109/ICCV.1995.466913Markdown
[Pajdla and Van Gool. "Matching of 3D Curves Using Semi-Differential Invariants." IEEE/CVF International Conference on Computer Vision, 1995.](https://mlanthology.org/iccv/1995/pajdla1995iccv-matching/) doi:10.1109/ICCV.1995.466913BibTeX
@inproceedings{pajdla1995iccv-matching,
title = {{Matching of 3D Curves Using Semi-Differential Invariants}},
author = {Pajdla, Tomás and Van Gool, Luc},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {1995},
pages = {390-395},
doi = {10.1109/ICCV.1995.466913},
url = {https://mlanthology.org/iccv/1995/pajdla1995iccv-matching/}
}