A New Evaluation Framework and Image Dataset for Keypoint Extraction and Feature Descriptor Matching

Iñigo Barandiaran, Camilo Cortes, Marcos Nieto, Manuel Graña, Oscar E. Ruiz

2013

Abstract

Key point extraction and description mechanisms play a crucial role in image matching, where several image points must be accurately identified to robustly estimate a transformation or to recognize an object or a scene. New procedures for keypoint extraction and for feature description are continuously emerging. In order to assess them accurately, normalized data and evaluation protocols are required. In response to these needs, we present a (1) new evaluation framework that allow assessing the performance of the state-of-the-art feature point extraction and description mechanisms, (2) a new image dataset acquired under controlled affine and photometric transformations and (3) a testing image generator. Our evaluation framework allows generating detailed curves about the performance of different approaches, providing a valuable insight about their behavior. Also, it can be easily integrated in many research and development environments. The contributions mentioned above are available on-line for the use of the scientific community.

Paper Citation

in Harvard Style

Barandiaran I., Cortes C., Nieto M., Graña M. and Ruiz O. (2013). A New Evaluation Framework and Image Dataset for Keypoint Extraction and Feature Descriptor Matching . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 252-257. DOI: 10.5220/0004211502520257

in Bibtex Style

@conference{visapp13,
author={Iñigo Barandiaran and Camilo Cortes and Marcos Nieto and Manuel Graña and Oscar E. Ruiz},
title={A New Evaluation Framework and Image Dataset for Keypoint Extraction and Feature Descriptor Matching},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={252-257},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004211502520257},
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 - A New Evaluation Framework and Image Dataset for Keypoint Extraction and Feature Descriptor Matching
SN - 978-989-8565-47-1
AU - Barandiaran I.
AU - Cortes C.
AU - Nieto M.
AU - Graña M.
AU - Ruiz O.
PY - 2013
SP - 252
EP - 257
DO - 10.5220/0004211502520257