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Harris 3D: a robust extension of the Harris operator for interest point detection on 3D meshes

Harris 3D: a robust extension of the Harris operator for interest point detection on 3D meshes With the increasing amount of 3D data and the ability of capture devices to produce low-cost multimedia data, the capability to select relevant information has become an interesting research field. In 3D objects, the aim is to detect a few salient structures which can be used, instead of the whole object, for applications like object registration, retrieval, and mesh simplification. In this paper, we present an interest points detector for 3D objects based on Harris operator, which has been used with good results in computer vision applications. We propose an adaptive technique to determine the neighborhood of a vertex, over which the Harris response on that vertex is calculated. Our method is robust to several transformations, which can be seen in the high repeatability values obtained using the SHREC feature detection and description benchmark. In addition, we show that Harris 3D outperforms the results obtained by recent effective techniques such as Heat Kernel Signatures. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Visual Computer Springer Journals

Harris 3D: a robust extension of the Harris operator for interest point detection on 3D meshes

Sipiran, Ivan; Bustos, Benjamin
The Visual Computer , Volume 27 (11) – Jul 1, 2011
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References (41)

Publisher
Springer Journals
Copyright
Copyright © 2011 by Springer-Verlag
Subject
Computer Science; Computer Graphics; Artificial Intelligence (incl. Robotics); Computer Science, general; Image Processing and Computer Vision
ISSN
0178-2789
eISSN
1432-2315
DOI
10.1007/s00371-011-0610-y
Publisher site
See Article on Publisher Site

Abstract

With the increasing amount of 3D data and the ability of capture devices to produce low-cost multimedia data, the capability to select relevant information has become an interesting research field. In 3D objects, the aim is to detect a few salient structures which can be used, instead of the whole object, for applications like object registration, retrieval, and mesh simplification. In this paper, we present an interest points detector for 3D objects based on Harris operator, which has been used with good results in computer vision applications. We propose an adaptive technique to determine the neighborhood of a vertex, over which the Harris response on that vertex is calculated. Our method is robust to several transformations, which can be seen in the high repeatability values obtained using the SHREC feature detection and description benchmark. In addition, we show that Harris 3D outperforms the results obtained by recent effective techniques such as Heat Kernel Signatures.

Journal

The Visual Computer – Springer Journals

Published: Jul 1, 2011

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