A RANSAC-Based Approach to Model Fitting and Its Application to Finding Cylinders in Range Data
Proceedings of the Seventh International Joint Conference on Artificial Intelligence. Vision: 3-d. Pages 637-642.
Abstract
General principles for filling models to data containing "gross" errors in addition to "measurement" errors are presented . A filling technique is described and illustrated by its application lo the problem of locating cylinders in range data ; lwo key steps in this process are filling ellipses lo partial data and filling lines to sets of three-dimensional points . The technique is specifically designed lo filter out gross errors before applying a smoothing procedure to compute a precise model. Such a technique is particularly applicable to computer vision tasks because the data in these tasks are often produced by local computations that are inherently unreliable.
@inproceedings{ijcai1981p119,
title = {A RANSAC-Based Approach to Model Fitting and Its Application to Finding Cylinders in Range Data},
author = {Bolles, Robert C. and Fischler, Martin A.},
booktitle = {Proceedings of the Seventh International Joint Conference on
Artificial Intelligence, {IJCAI-81}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Roger C. Schank},
pages = {637--642},
year = {1981},
month = {8},
note = {Vision: 3-d},
url = {https://ijcai.org/proceedings/1981/119},
}
TY - CPAPER TI - A RANSAC-Based Approach to Model Fitting and Its Application to Finding Cylinders in Range Data AU - Bolles, Robert C. AU - Fischler, Martin A. T2 - Proceedings of the Seventh International Joint Conference on Artificial Intelligence, IJCAI-81 PB - International Joint Conferences on Artificial Intelligence PY - 1981 SP - 637 EP - 642 UR - https://ijcai.org/proceedings/1981/119 ER -Copied
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