Scalable Symmetry Detection for Urban Scenes. (9th October 2012)

• Record Type: Journal Article
• Authors: Kerber, J.; Bokeloh, M.; Wand, M.; Seidel, H.‐P.
• Is Part Of: Computer graphics forum. Volume 32:Number 1(2013)
• Page Start: 3
• Page End: 15
• Publication Date: 2012-10-09
• Subjects: Computer graphics -- Periodicals; 006.605
• DOI: 10.1111/j.1467-8659.2012.03226.x
• Languages: English
• ISSNs: 0167-7055

Abstract

<abstract abstract-type="main" xml:lang="en"> <title>Abstract</title> <p> <italic>In this paper, we present a novel method for detecting partial symmetries in very large point clouds of 3D city scans. Unlike previous work, which has only been demonstrated on data sets of a few hundred megabytes maximum, our method scales to very large scenes: We map the detection problem to a nearest‐neighbour problem in a low‐dimensional feature space, and follow this with 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 that of state‐of‐the‐art methods. In practice, it scales linearly with scene size and achieves a high absolute throughput, processing half a terabyte of scanner data overnight on a dual socket commodity PC.</italic> </p> </abstract>