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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Abstract
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/116971/ | |||||||||||||||
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Document Type: | Conference or Workshop Item (Speech) | |||||||||||||||
Title: | Eligible Features Segregation for Real-time Visual Odometry | |||||||||||||||
Authors: |
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Date: | December 2017 | |||||||||||||||
Refereed publication: | No | |||||||||||||||
Open Access: | Yes | |||||||||||||||
Gold Open Access: | No | |||||||||||||||
In SCOPUS: | No | |||||||||||||||
In ISI Web of Science: | No | |||||||||||||||
Status: | Published | |||||||||||||||
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: | 12 Dec 2017 10:14 | |||||||||||||||
Last Modified: | 27 Jan 2020 13:38 |
Available Versions of this Item
- Eligible Features Segregation for Real-time Visual Odometry. (deposited 12 Dec 2017 10:14) [Currently Displayed]
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