IMAGE UNDERSTANDING USING SELF-SIMILAR SIFT FEATURES

Nils Hering, Frank Schmitt, Lutz Priese

2009

Abstract

In this paper we present a new method to group self-similar SIFT features in images. The aim is to automatically build groups of all SIFT features with the same semantics in an image. To achieve this a new distance between SIFT feature vectors taking into account their orientation and scale is introduced. The methods are presented in the context of recognition of buildings. A first evaluation shows promising results.

Paper Citation

in Harvard Style

Hering N., Schmitt F. and Priese L. (2009). IMAGE UNDERSTANDING USING SELF-SIMILAR SIFT FEATURES . In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009) ISBN 978-989-8111-69-2, pages 114-119. DOI: 10.5220/0001753501140119

in Bibtex Style

@conference{visapp09,
author={Nils Hering and Frank Schmitt and Lutz Priese},
title={IMAGE UNDERSTANDING USING SELF-SIMILAR SIFT FEATURES},
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)},
year={2009},
pages={114-119},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001753501140119},
isbn={978-989-8111-69-2},
}

in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)
TI - IMAGE UNDERSTANDING USING SELF-SIMILAR SIFT FEATURES
SN - 978-989-8111-69-2
AU - Hering N.
AU - Schmitt F.
AU - Priese L.
PY - 2009
SP - 114
EP - 119
DO - 10.5220/0001753501140119