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D. Schröter and M. Beetz. Acquiring Modells of Rectangular Objects for Robot Maps. In Proc. of IEEE International Conference on Robotics and Automation (ICRA), New Orleans/USA, 2004.

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Abstract

State-of-the-art robot mapping approaches are capable of acquiringimpressively accurate 2D and 3D models of their environments. To the best ofour knowledge few of them can acquire models of task-relevant objects.In this paper, we introduce a novel method for acquiring models oftask-relevant objects from stereo images. The proposed algorithmapplies methods from projective geometry and works for rectangularobjects, which are, in office- and museum-like environments,the most commonly found subclass of geometric objects.The method is shown to work accurately and for a wide range ofviewing angles and distances.

BibTeX Entry

@InProceedings{ SchroeterIcra04RectObjects,
author = {D. Schr{\"o}ter and M. Beetz},
title = {{Acquiring Modells of Rectangular Objects for Robot Maps}},
booktitle = {Proc. of IEEE International Conference on Robotics and Automation (ICRA), New Orleans/USA},
year = {2004},
abstract = {{State-of-the-art robot mapping approaches are capable of acquiring
impressively accurate 2D and 3D models of their environments. To the best of
our knowledge few of them can acquire models of task-relevant objects.
In this paper, we introduce a novel method for acquiring models of
task-relevant objects from stereo images. The proposed algorithm
applies methods from projective geometry and works for rectangular
objects, which are, in office- and museum-like environments,
the most commonly found subclass of geometric objects.
The method is shown to work accurately and for a wide range of
viewing angles and distances.}},
bib2html_pubtype  = {Refereed Conference Paper},
bib2html_rescat   = {Robot Mapping},
bib2html_groups   = {IAS,EvI},
bib2html_funding  = {EvI},
bib2html_keywords = {Environment Mapping},
}

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