STRUCTURAL ICP ALGORITHM FOR POSE ESTIMATION BASED ON LOCAL FEATURES

Marco A. Chavarria, Gerald Sommer

Abstract

In this paper we present a new variant of the ICP (iterative closest point) algorithm for finding correspondences between image and model points. This new variant uses structural information from the model points and contour segments detected in images to find better conditioned correspondence sets and to use them to compute the 3D pose. A local representation of 3D free-form contours is used to get the structural information in 3D space and in the image plane. Furthermore, the local structure of free-form contours is combined with orientation and phase as local features obtained from the monogenic signal. With this combination, we achieve a more robust correspondence search. Our approach was tested on synthetical and real data to compare the convergence and performance of our approach against the classical ICP approach.

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Paper Citation


in Harvard Style

A. Chavarria M. and Sommer G. (2007). STRUCTURAL ICP ALGORITHM FOR POSE ESTIMATION BASED ON LOCAL FEATURES . In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 978-972-8865-74-0, pages 341-346. DOI: 10.5220/0002045003410346


in Bibtex Style

@conference{visapp07,
author={Marco A. Chavarria and Gerald Sommer},
title={STRUCTURAL ICP ALGORITHM FOR POSE ESTIMATION BASED ON LOCAL FEATURES},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2007},
pages={341-346},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002045003410346},
isbn={978-972-8865-74-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - STRUCTURAL ICP ALGORITHM FOR POSE ESTIMATION BASED ON LOCAL FEATURES
SN - 978-972-8865-74-0
AU - A. Chavarria M.
AU - Sommer G.
PY - 2007
SP - 341
EP - 346
DO - 10.5220/0002045003410346