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3D Cueing: A Data Filter For Object Recognition

Owen Carmichael and Martial Hebert
Conference Paper, IEEE Conference on Robotics and Automation (ICRA '99), Vol. 2, pp. 944 - 950, May, 1999

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Abstract

Presents a method for quickly filtering range data points to make object recognition in large 3D data sets feasible. The general approach, called “3D cueing”, uses shape signatures from object models as the basis for a fast, probabilistic classification system which rates scene points in terms of their likelihood of belonging to a model. This algorithm which could be used as a front-end for any traditional 3D matching technique, is demonstrated using several models and cluttered scenes in which the model occupies between 1% and 50% of the data points.

BibTeX Reference
@conference{Carmichael-1999-14905,
title = {3D Cueing: A Data Filter For Object Recognition},
author = {Owen Carmichael and Martial Hebert},
booktitle = {IEEE Conference on Robotics and Automation (ICRA '99)},
keyword = {object recognition,range data, cueing, data filtering},
month = {May},
year = {1999},
volume = {2},
pages = {944 - 950},
}
2017-09-13T10:48:56+00:00