CUED Publications database

Scale-invariant vote-based 3D recognition and registration from point clouds

Pham, M-T and Woodford, OJ and Perbet, F and Maki, A and Gherardi, R and Stenger, B and Cipolla, R (2013) Scale-invariant vote-based 3D recognition and registration from point clouds. Studies in Computational Intelligence, 411. pp. 137-162. ISSN 1860-949X

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Abstract

This chapter presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transformations for the first time. We introduce a new distance between poses in this spacethe SRT distance. It is left-invariant, unlike Euclidean distance, and has a unique, closed-form mean, in contrast to Riemannian distance, so is fast to compute. We demonstrate improved performance over the state of the art in both recognition and registration on a (real and) challenging dataset, by comparing our distance with others in a mean shift framework, as well as with the commonly used Hough voting approach. © 2013 Springer-Verlag Berlin Heidelberg.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div F > Machine Intelligence
Depositing User: Cron Job
Date Deposited: 07 Mar 2014 12:20
Last Modified: 08 Dec 2014 02:35
DOI: 10.1007/978-3-642-28661-2-6