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Manhattan Scene Understanding Using Monocular, Stereo, and 3D Features

Abstract:

This paper addresses scene understanding in the context of a moving camera, integrating semantic reasoning ideas from monocular vision with 3D information available through structure-from-motion. We combine geometric and photometric cues in a Bayesian framework, building on recent successes leveraging the indoor Manhattan assumption in monocular vision. We focus on indoor environments and show how to extract key boundaries while ignoring clutter and decorations. To achieve this we present a g...

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Publication status:
Published

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Publisher copy:
10.1109/ICCV.2011.6126501

Authors


Pages:
2228-2235
Publication date:
2011
DOI:
URN:
uuid:17826ba5-023f-4ec1-9a8a-fc00193a0988
Source identifiers:
313974
Local pid:
pubs:313974
ISBN:
9781457711015

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