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Geometric Reasoning for Single Image Structure Recovery

David Changsoo Lee, Martial Hebert and Takeo Kanade
Conference Paper, Carnegie Mellon University, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June, 2009

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Abstract

We study the problem of generating plausible interpretations of a scene from a collection of line segments automatically extracted from a single indoor image. We show that we can recognize the three dimensional structure of the interior of a building, even in the presence of occluding objects. Several physically valid structure hypotheses are proposed by geometric reasoning and verified to find the best fitting model to line segments, which is then converted to a full 3D model. Our experiments demonstrate that our structure recovery from line segments is comparable with methods using full image appearance. Our approach shows how a set of rules describing geometric constraints between groups of segments can be used to prune scene interpretation hypotheses and to generate the most plausible interpretation.

BibTeX Reference
@conference{Lee-2009-10231,
title = {Geometric Reasoning for Single Image Structure Recovery},
author = {David Changsoo Lee and Martial Hebert and Takeo Kanade},
booktitle = {IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)},
school = {Robotics Institute , Carnegie Mellon University},
month = {June},
year = {2009},
address = {Pittsburgh, PA},
}
2017-09-13T10:41:10+00:00