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Robust Edge-based Visual Odometry using Machine-Learned Edges

Schenk, Fabian and Fraundorfer, Friedrich (2017) Robust Edge-based Visual Odometry using Machine-Learned Edges. In: Proceedings IEEE/RSJ, pp. 1-8. International Conference on Intelligent Robots and Systems (IROS) 2017, 24.-28.Sep. 2017, Vancouver, Kanada.

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Abstract

In this work, we present a real-time robust edgebased visual odometry framework for RGBD sensors (REVO). Even though our method is independent of the edge detection algorithm, we show that the use of state-of-the-art machinelearned edges gives significant improvements in terms of robustness and accuracy compared to standard edge detection methods. In contrast to approaches that heavily rely on the photo-consistency assumption, edges are less influenced by lighting changes and the sparse edge representation offers a larger convergence basin while the pose estimates are also very fast to compute. Further, we introduce a measure for tracking quality, which we use to determine when to insert a new key frame. We show the feasibility of our system on realworld datasets and extensively evaluate on standard benchmark sequences to demonstrate the performance in a wide variety of scenes and camera motions. Our framework runs in real-time on the CPU of a laptop computer and is available online.

Item URL in elib:https://elib.dlr.de/115764/
Document Type:Conference or Workshop Item (Speech)
Title:Robust Edge-based Visual Odometry using Machine-Learned Edges
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Schenk, Fabianschenk (at) icg.tu-graz.ac.atUNSPECIFIED
Fraundorfer, Friedrichfriedrich.fraundorfer (at) dlr.deUNSPECIFIED
Date:2017
Journal or Publication Title:Proceedings IEEE/RSJ
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 1-8
Status:Published
Keywords:Robust Edge-based Visual Odometry, Machine-Learned Edges
Event Title:International Conference on Intelligent Robots and Systems (IROS) 2017
Event Location:Vancouver, Kanada
Event Type:international Conference
Event Dates:24.-28.Sep. 2017
Organizer:IEEE/RSJ
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:01 Dec 2017 16:53
Last Modified:31 Jul 2019 20:13

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