Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization (bibtex)
by L. von Stumberg, V. Usenko and D. Cremers
Reference:
Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization (L. von Stumberg, V. Usenko and D. Cremers), In International Conference on Robotics and Automation (ICRA), 2018. ([supplementary][video][arxiv])
Bibtex Entry:
@string{icra="International Conference on Robotics and Automation (ICRA)"}
@inproceedings{stumberg18vidso,
 author = {L. von Stumberg and V. Usenko and D. Cremers},
 title = {Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization},
 booktitle = {International Conference on Robotics and Automation (ICRA)},
 year = {2018},
 month = {May},
 keywords = {dso, vi-dso, vslam},
}
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Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization (bibtex)
Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization (bibtex)
by L. von Stumberg, V. Usenko and D. Cremers
Reference:
Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization (L. von Stumberg, V. Usenko and D. Cremers), In International Conference on Robotics and Automation (ICRA), 2018. ([supplementary][video][arxiv])
Bibtex Entry:
@string{icra="International Conference on Robotics and Automation (ICRA)"}
@inproceedings{stumberg18vidso,
 author = {L. von Stumberg and V. Usenko and D. Cremers},
 title = {Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization},
 booktitle = {International Conference on Robotics and Automation (ICRA)},
 year = {2018},
 month = {May},
 keywords = {dso, vi-dso, vslam},
}
Powered by bibtexbrowser
members:stumberg

Table of Contents

Lukas von Stumberg

PhD Student

Technical University of Munich

School of Computation, Information and Technology
Informatics 9
Boltzmannstrasse 3
85748 Garching
Germany

Fax: +49-89-289-17757
Office: 
Mail: stumberg@in.tum.de

Find me on Google Scholar Linkedin

Research Interests

My research interests are visual and visual-inertial SLAM, robotics, and 3D reconstruction. I like to apply both traditional methods and deep learning.

Selected Projects

GN-Net: The Gauss-Newton Loss for Multi-Weather Relocalization

Using our novel Gauss-Newton loss we improve the robustness of direct methods against strong illumination changes and bad initializations. This allows us to accurately relocalize between different weathers. Project Page



VI-DSO: Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization

In my Master thesis on direct visual-inertial odometry we demonstrate state-of-the-art performance on the EuRoC dataset. Project Page



From Monocular SLAM to Autonomous Drone Exploration

In my Bachelor thesis I have used LSD-SLAM to explore an unknown environment with an autonomous drone.