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Eligible Features Segregation for Real-time Visual Odometry

Zhang, Hongmou and Wohlfeil, Jürgen and Grießbach, Denis and Börner, Anko (2017) Eligible Features Segregation for Real-time Visual Odometry. 3D-NordOst 2017, Berlin, Germany.

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Stereo vision aided inertial navigation enables accurate self-localization and navigation in unknown environment without the need of positioning systems (e.g. GNSS). The feature extractor is an elementary part of this technology because it extracts the landmarks from the camera images, which are then used for optical navigation. This is why the feature extractor is usually the first module of data processing chain. In most of the cases, the features from the feature extractor are filtered by a non-maximum suppression algorithm. An ideal non-maximum suppression algorithm suppresses "weak" features while keeping "strong" and well-distributed features. Only if the feature extractor is combined with an appropriate non-maximum suppression module, the computer vision system can get reasonably good results. In this paper, we propose a novel non-maximum suppression algorithm. The algorithm does not only provide well-distributed features over the whole image but is also be able to control the maximum number of required features in output, which is very important for real-time system. We apply our framework to the AGAST feature extraction algorithm, and it is very easy to incorporate with other feature extractors. Finally, we combine our algorithm with the Integrated Positioning System (IPS) which is developed by the German Aerospace Center (DLR). The comparison of testing results is illustrated.

Item URL in elib:https://elib.dlr.de/133894/
Document Type:Conference or Workshop Item (Speech)
Title:Eligible Features Segregation for Real-time Visual Odometry
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Zhang, HongmouHongmou.Zhang (at) dlr.dehttps://orcid.org/0000-0001-8284-5119
Wohlfeil, Jürgenjuergen.wohlfeil (at) dlr.dehttps://orcid.org/0000-0003-1786-6460
Grießbach, Denisdenis.griessbach (at) dlr.deUNSPECIFIED
Börner, Ankoanko.boerner (at) dlr.deUNSPECIFIED
Date:December 2017
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:non-maximum suppression, feature detector, Integrated Positioning System, optical navigation
Event Title:3D-NordOst 2017
Event Location:Berlin, Germany
Event Type:Workshop
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Optical Technologies and Applications
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Optical Sensor Systems > Real-Time Data Processing
Deposited By: Zhang, Hongmou
Deposited On:28 Jan 2020 08:42
Last Modified:28 Jan 2020 08:42

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