Robust Reconstruction of Interior Building Structures with Multiple Rooms under Clutter and Occlusions

We present a robust approach for reconstructing the architectural structure of complex indoor environments given a set of cluttered input scans. Our method first uses an efficient occlusion-aware process to extract planar patches as candidate walls, separating them from clutter and coping with missi...

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Bibliographic Details
Published in2013 International Conference on Computer-Aided Design and Computer Graphics pp. 52 - 59
Main Authors Mura, Claudio, Mattausch, Oliver, Villanueva, Alberto Jaspe, Gobbetti, Enrico, Pajarola, Renato
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2013
Subjects
Buildings
Clutter
Data models
indoor scene reconstruction
LIDAR reconstruction
point cloud processing
Robustness
Shape
Solid modeling
Three-dimensional displays
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DOI10.1109/CADGraphics.2013.14

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Summary:We present a robust approach for reconstructing the architectural structure of complex indoor environments given a set of cluttered input scans. Our method first uses an efficient occlusion-aware process to extract planar patches as candidate walls, separating them from clutter and coping with missing data. Using a diffusion process to further increase its robustness, our algorithm is able to reconstruct a clean architectural model from the candidate walls. To our knowledge, this is the first indoor reconstruction method which goes beyond a binary classification and automatically recognizes different rooms as separate components. We demonstrate the validity of our approach by testing it on both synthetic models and real-world 3D scans of indoor environments.
DOI:10.1109/CADGraphics.2013.14