Robust odometry estimation for RGB-D cameras
Kerl C, Sturm J, Cremers D (2013)
Publication Type: Conference contribution
Publication year: 2013
Journal
Pages Range: 3748-3754
Conference Proceedings Title: Proceedings - IEEE International Conference on Robotics and Automation
Event location: DEU
ISBN: 9781467356411
DOI: 10.1109/ICRA.2013.6631104
Abstract
The goal of our work is to provide a fast and accurate method to estimate the camera motion from RGB-D images. Our approach registers two consecutive RGB-D frames directly upon each other by minimizing the photometric error. We estimate the camera motion using non-linear minimization in combination with a coarse-to-fine scheme. To allow for noise and outliers in the image data, we propose to use a robust error function that reduces the influence of large residuals. Furthermore, our formulation allows for the inclusion of a motion model which can be based on prior knowledge, temporal filtering, or additional sensors like an IMU. Our method is attractive for robots with limited computational resources as it runs in real-time on a single CPU core and has a small, constant memory footprint. In an extensive set of experiments carried out both on a benchmark dataset and synthetic data, we demonstrate that our approach is more accurate and robust than previous methods. We provide our software under an open source license. © 2013 IEEE.
Involved external institutions
Germany (DE)How to cite
APA:
Kerl, C., Sturm, J., & Cremers, D. (2013). Robust odometry estimation for RGB-D cameras. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 3748-3754). DEU.
MLA:
Kerl, Christian, Jurgen Sturm, and Daniel Cremers. "Robust odometry estimation for RGB-D cameras." Proceedings of the 2013 IEEE International Conference on Robotics and Automation, ICRA 2013, DEU 2013. 3748-3754.
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