Keypoints Detection in RGB-D Space - A Hybrid Approach

Nizar Sallem, Michel Devy, Radu Rusu, Suat Gedikili

2013

Abstract

Features detection is an important technique of image processing which aim is to find a subset, often discrete, of a query image satisfying uniqueness and discrimination criteria so that an image can be abstracted to the computed features. Detected features are then used in video indexing, registration, object and scene reconstruction, structure from motion, etc. In this article we discuss the definition and implementation of such features in the RGB-Depth space RGB-D.We focus on the corners as they are the most used features in image processing. We show the advantage of using 3D data over image only techniques and the power of combining geometric and colorimetric information to find corners in a scene.

Paper Citation

in Harvard Style

Sallem N., Devy M., Gedikili S. and Rusu R. (2013). Keypoints Detection in RGB-D Space - A Hybrid Approach . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 496-499. DOI: 10.5220/0004305004960499

in Bibtex Style

@conference{visapp13,
author={Nizar Sallem and Michel Devy and Suat Gedikili and Radu Rusu},
title={Keypoints Detection in RGB-D Space - A Hybrid Approach},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={496-499},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004305004960499},
isbn={978-989-8565-47-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - Keypoints Detection in RGB-D Space - A Hybrid Approach
SN - 978-989-8565-47-1
AU - Sallem N.
AU - Devy M.
AU - Gedikili S.
AU - Rusu R.
PY - 2013
SP - 496
EP - 499
DO - 10.5220/0004305004960499