Integrating Kinect Depth Data with a Stochastic Object Classification Framework for Forestry Robots

Mostafa Pordel, Thomas Hellström, Ahmad Ostovar

2012

Abstract

In this paper we study the integration of a depth sensor and an RGB camera for a stochastic classification system for forestry robots. The images are classified as bush, tree, stone and human and are expected to come from a robot working in forest environment. A set of features is extracted from labeled images to train a number of stochastic classifiers. The outputs of the classifiers are then combined in a meta-classifier to produce the final result. The results show that using depth information in addition to the RGB results in higher classification performance.

Paper Citation

in Harvard Style

Pordel M., Hellström T. and Ostovar A. (2012). Integrating Kinect Depth Data with a Stochastic Object Classification Framework for Forestry Robots . In Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-8565-22-8, pages 314-320. DOI: 10.5220/0004045203140320

in Bibtex Style

@conference{icinco12,
author={Mostafa Pordel and Thomas Hellström and Ahmad Ostovar},
title={Integrating Kinect Depth Data with a Stochastic Object Classification Framework for Forestry Robots},
booktitle={Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2012},
pages={314-320},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004045203140320},
isbn={978-989-8565-22-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Integrating Kinect Depth Data with a Stochastic Object Classification Framework for Forestry Robots
SN - 978-989-8565-22-8
AU - Pordel M.
AU - Hellström T.
AU - Ostovar A.
PY - 2012
SP - 314
EP - 320
DO - 10.5220/0004045203140320