Image Features in Space - Evaluation of Feature Algorithms for Motion Estimation in Space Scenarios

Marc Steven Krämer, Simon Hardt, Klaus-Dieter Kuhnert

Abstract

Image features are used in many computer vision applications. One important field of use is the visual navigation. The localization of robots can be done with the help of visual odometry. To detect its surrounding, a robot is typically equipped with different environment sensors like cameras or lidar. For such a multi sensor system the exact pose of each sensor is very important. To test, monitor and correct these calibration parameters, the ego-motion can be calculated separately by each sensor and compared. In this study we evaluate SIFT, SURF, ORB, AKAZE, BRISK, BRIEF and KAZE operator for visual odometry in a space scenario. Since there was no suitable space test data available, we have generated our own.

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Paper Citation


in Harvard Style

Krämer M., Hardt S. and Kuhnert K. (2018). Image Features in Space - Evaluation of Feature Algorithms for Motion Estimation in Space Scenarios.In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-276-9, pages 300-308. DOI: 10.5220/0006555303000308


in Bibtex Style

@conference{icpram18,
author={Marc Steven Krämer and Simon Hardt and Klaus-Dieter Kuhnert},
title={Image Features in Space - Evaluation of Feature Algorithms for Motion Estimation in Space Scenarios},
booktitle={Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2018},
pages={300-308},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006555303000308},
isbn={978-989-758-276-9},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Image Features in Space - Evaluation of Feature Algorithms for Motion Estimation in Space Scenarios
SN - 978-989-758-276-9
AU - Krämer M.
AU - Hardt S.
AU - Kuhnert K.
PY - 2018
SP - 300
EP - 308
DO - 10.5220/0006555303000308