Pose Clustering From Stereo Data

Ulrich Hillenbrand



This article describes an algorithm for pose or motion estimation based on clustering of parameters in the six-dimensional pose space. The parameter samples are computed from data samples randomly drawn from stereo data points. The estimator is global and robust, performing matches to parts of a scene without prior pose information. It is general, in that it does not require any particular object features. Empirical object models can be built largely automatically. An implemented application from the service robotic domain and a quantitative performance study on real data are presented.


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Paper Citation

in Harvard Style

Hillenbrand U. (2008). Pose Clustering From Stereo Data . In VISAPP-Robotic Perception - Volume 1: VISAPP-RoboPerc, (VISIGRAPP 2008) ISBN 978-989-8111-23-4, pages 23-32. DOI: 10.5220/0002341900230032

in Bibtex Style

author={Ulrich Hillenbrand},
title={Pose Clustering From Stereo Data},
booktitle={VISAPP-Robotic Perception - Volume 1: VISAPP-RoboPerc, (VISIGRAPP 2008)},

in EndNote Style

JO - VISAPP-Robotic Perception - Volume 1: VISAPP-RoboPerc, (VISIGRAPP 2008)
TI - Pose Clustering From Stereo Data
SN - 978-989-8111-23-4
AU - Hillenbrand U.
PY - 2008
SP - 23
EP - 32
DO - 10.5220/0002341900230032