Comparing Curved-Surface Range Image Segmenters
Abstract
This work focuses on creating a framework for objectively evaluating the performance of range image segmentation algorithms. The algorithms are evaluated in terms of correct segmentation, over- and under-segmentation, missed and noise regions. A set of images with ground truth was created for this work. The images were captured using a structured light scanner. Images used in the evaluation contain planar, spherical, cylindrical, toroidal and conical surface patches. The different surface patches in each image were manually identified to establish ground truth for performance evaluation. Two segmentation algorithms from the literature are compared.
Cite
Text
Powell et al. "Comparing Curved-Surface Range Image Segmenters." IEEE/CVF International Conference on Computer Vision, 1998. doi:10.1109/ICCV.1998.710732Markdown
[Powell et al. "Comparing Curved-Surface Range Image Segmenters." IEEE/CVF International Conference on Computer Vision, 1998.](https://mlanthology.org/iccv/1998/powell1998iccv-comparing/) doi:10.1109/ICCV.1998.710732BibTeX
@inproceedings{powell1998iccv-comparing,
title = {{Comparing Curved-Surface Range Image Segmenters}},
author = {Powell, Mark W. and Bowyer, Kevin W. and Jiang, Xiaoyi and Bunke, Horst},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {1998},
pages = {286-291},
doi = {10.1109/ICCV.1998.710732},
url = {https://mlanthology.org/iccv/1998/powell1998iccv-comparing/}
}