Scene Reconstruction and Description: Geometric Primitive Extraction from Multiple Viewed Scattered Data
Abstract
Robust extraction of surface parameters from multiple view scattered and noisy 3-D measurements is a delicate task. It is shown that a stable local surface description can be extracted on sections where measurement constraints are redundant with respect to a polynomial model. A segmentation approach is developed to identify these sections. The approach is based on a measurement error model which takes into account the sensor's viewpoint. An application of the approach to the extraction of straight line sections from single scan 3-D surface profiles is presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Hébert et al. "Scene Reconstruction and Description: Geometric Primitive Extraction from Multiple Viewed Scattered Data." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993. doi:10.1109/CVPR.1993.340967Markdown
[Hébert et al. "Scene Reconstruction and Description: Geometric Primitive Extraction from Multiple Viewed Scattered Data." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993.](https://mlanthology.org/cvpr/1993/hebert1993cvpr-scene/) doi:10.1109/CVPR.1993.340967BibTeX
@inproceedings{hebert1993cvpr-scene,
title = {{Scene Reconstruction and Description: Geometric Primitive Extraction from Multiple Viewed Scattered Data}},
author = {Hébert, Patrick and Laurendeau, Denis and Poussart, Denis},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1993},
pages = {286-292},
doi = {10.1109/CVPR.1993.340967},
url = {https://mlanthology.org/cvpr/1993/hebert1993cvpr-scene/}
}