GRAPH MATCHING USING SIFT DESCRIPTORS - An Application to Pose Recovery of a Mobile Robot

Gerard Sanromà, René Alquézar, Francesc Serratosa

Abstract

Image-feature matching based on Local Invariant Feature Extraction (LIFE) methods has proven to be successful, and SIFT is one of the most effective. SIFT matching uses only local texture information to compute the correspondences. A number of approaches have been presented aimed at enhancing the image-features matches computed using only local information such as SIFT. What most of these approaches have in common is that they use a higher level information such as spatial arrangement of the feature points to reject a subset of outliers. The main limitation of the outlier rejectors is that they are not able to enhance the configuration of matches by adding new useful ones. In the present work we propose a graph matching algorithm aimed not only at rejecting erroneous matches but also at selecting additional useful ones. We use both the graph structure to encode the geometrical information and the SIFT descriptors in the node's attributes to provide local texture information. This algorithm is an ensemble of successful ideas previously reported by other researchers. We demonstrate the effectiveness of our algorithm in a pose recovery application.

References

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Paper Citation


in Harvard Style

Sanromà G., Alquézar R. and Serratosa F. (2010). GRAPH MATCHING USING SIFT DESCRIPTORS - An Application to Pose Recovery of a Mobile Robot . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-029-0, pages 249-254. DOI: 10.5220/0002829702490254


in Bibtex Style

@conference{visapp10,
author={Gerard Sanromà and René Alquézar and Francesc Serratosa},
title={GRAPH MATCHING USING SIFT DESCRIPTORS - An Application to Pose Recovery of a Mobile Robot},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={249-254},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002829702490254},
isbn={978-989-674-029-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)
TI - GRAPH MATCHING USING SIFT DESCRIPTORS - An Application to Pose Recovery of a Mobile Robot
SN - 978-989-674-029-0
AU - Sanromà G.
AU - Alquézar R.
AU - Serratosa F.
PY - 2010
SP - 249
EP - 254
DO - 10.5220/0002829702490254