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Combining Edge Images and Depth Maps for Robust Visual Odometry

Schenk, Fabian and Fraundorfer, Friedrich (2017) Combining Edge Images and Depth Maps for Robust Visual Odometry. In: Proceedings 28th British Machine Vision Conference, pp. 1-12. 28th British Machine Vision Conference, 04.-07. Sep. 2017, London, UK.

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Official URL: https://bmvc2017.london/


In this work, we propose a robust visual odometry system for RGBD sensors. The core of our method is a combination of edge images and depth maps for joint camera pose estimation. Edges are more stable under varying lighting conditions than raw intensity values and depth maps further add stability in poorly textured environments. This leads to higher accuracy and robustness in scenes, where feature- or photoconsistency-based approaches often fail. We demonstrate the robustness of our method under challenging conditions on various real-world scenarios recorded with our own RGBD sensor. Further, we evaluate on several sequences from standard benchmark datasets covering a wide variety of scenes and camera motions. The results show that our method performs best in terms of trajectory accuracy for most of the sequences indicating that the chosen combination of edge and depth terms in the cost function is suitable for a multitude of scenes.

Item URL in elib:https://elib.dlr.de/115945/
Document Type:Conference or Workshop Item (Speech)
Title:Combining Edge Images and Depth Maps for Robust Visual Odometry
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Schenk, Fabianschenk (at) icg.tu-graz.ac.atUNSPECIFIED
Fraundorfer, Friedrichfriedrich.fraundorfer (at) dlr.deUNSPECIFIED
Journal or Publication Title:Proceedings 28th British Machine Vision Conference
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1-12
Keywords:Edge Images, Depth Maps, Robust Visual Odometry System, RGBD sensors
Event Title:28th British Machine Vision Conference
Event Location:London, UK
Event Type:international Conference
Event Dates:04.-07. Sep. 2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - Vabene++ (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Zielske, Mandy
Deposited On:29 Nov 2017 17:29
Last Modified:31 Jul 2019 20:13

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