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Symmetry Detection in Large Scale City Scans

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44758

Kerber,  Jens
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45695

Wand,  Michael
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45449

Seidel,  Hans-Peter
Computer Graphics, MPI for Informatics, Max Planck Society;

Externe Ressourcen
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Volltexte (frei zugänglich)

MPI-I-2012-4-001.pdf
(beliebiger Volltext), 14MB

Ergänzendes Material (frei zugänglich)
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Zitation

Kerber, J., Wand, M., Bokeloh, M., & Seidel, H.-P.(2012). Symmetry Detection in Large Scale City Scans (MPI-I-2012-4-001).


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0024-0427-4
Zusammenfassung
In this report we present a novel method for detecting partial symmetries in very large point clouds of 3D city scans. Unlike previous work, which was limited to data sets of a few hundred megabytes maximum, our method scales to very large scenes. We map the detection problem to a nearestneighbor search in a low-dimensional feature space, followed by a cascade of tests for geometric clustering of potential matches. Our algorithm robustly handles noisy real-world scanner data, obtaining a recognition performance comparable to state-of-the-art methods. In practice, it scales linearly with the scene size and achieves a high absolute throughput, processing half a terabyte of raw scanner data over night on a dual socket commodity PC.