Adaptive SLAM with Synthetic Stereo Dataset Generation for Real-time Dense 3D Reconstruction

Antoine Billy, Sébastien Pouteau, Pascal Desbarats, Serge Chaumette, Jean-Philippe Domenger

2019

Abstract

In robotic mapping and navigation, of prime importance today with the trend for autonomous cars, simultaneous localization and mapping (SLAM) algorithms often use stereo vision to extract 3D information of the surrounding world. Whereas the number of creative methods for stereo-based SLAM is continuously increasing, the variety of datasets is relatively poor and the size of their contents relatively small. This size issue is increasingly problematic, with the recent explosion of deep learning based approaches, several methods require an important amount of data. Those multiple techniques contribute to enhance the precision of both localization estimation and mapping estimation to a point where the accuracy of the sensors used to get the ground truth might be questioned. Finally, because today most of these technologies are embedded on on-board systems, the power consumption and real-time constraints turn to be key requirements. Our contribution is twofold: we propose an adaptive SLAM method that reduces the number of processed frame with minimum impact error, and we make available a synthetic flexible stereo dataset with absolute ground truth, which allows to run new benchmarks for visual odometry challenges. This dataset is available online at http://alastor.labri.fr/.

Paper Citation

in Harvard Style

Billy A., Pouteau S., Desbarats P., Chaumette S. and Domenger J. (2019). Adaptive SLAM with Synthetic Stereo Dataset Generation for Real-time Dense 3D Reconstruction. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4, SciTePress, pages 840-848. DOI: 10.5220/0007386508400848

in Bibtex Style

@conference{visapp19,
author={Antoine Billy and Sébastien Pouteau and Pascal Desbarats and Serge Chaumette and Jean-Philippe Domenger},
title={Adaptive SLAM with Synthetic Stereo Dataset Generation for Real-time Dense 3D Reconstruction},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={840-848},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007386508400848},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Adaptive SLAM with Synthetic Stereo Dataset Generation for Real-time Dense 3D Reconstruction
SN - 978-989-758-354-4
AU - Billy A.
AU - Pouteau S.
AU - Desbarats P.
AU - Chaumette S.
AU - Domenger J.
PY - 2019
SP - 840
EP - 848
DO - 10.5220/0007386508400848
PB - SciTePress