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Uncertainty Model for Template Feature Matching

Zhang, Hongmou and Grießbach, Denis and Wohlfeil, Jürgen and Börner, Anko (2017) Uncertainty Model for Template Feature Matching. The Pacific-Rim Symposium on Image and Video Technology 2017, 20-24 Nov 2017, Wuhan, China. (In Press)

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Abstract

Using visual odometry and inertial measurements, indoor and outdoor positioning systems can perform an accurate self-localization in unknown, unstructured environments where absolute positioning systems (e.g. GNSS) are unavailable. However, the achievable accuracy is highly affected by the residuals of calibration, the quality of the noise model, etc. Only if these unavoidable uncertainties of sensors and data processing can be taken into account and be handled via error propagation, which allows to propagate them through the entire system. The central filter (e.g. Kalman filter) of the system can then make use of the enhanced statistical model and use the propagated errors to calculate the optimal result. In this paper, we focus on the uncertaintiy calculation of the elementary part of the optical navigation, the template feature matcher. First of all, we propose a method to model the image noise. Then we use Taylor's theorem to extend two very popular and efficient template feature matchers sum-of-absolute-differences (SAD) and normalized-cross-correlation (NCC) to get sub-pixel matching results. Based on the proposed noise model and the extended matcher, we propagate the image noise to the uncertainties of sub-pixel matching results. Although the SAD and NCC are used, the image noise model can be easily combined with other feature matchers. We evaluate our method by an Integrated Positioning System (IPS) which is developed by German Aerospace Center. The experimental results show that our method can improve the quality of the measured trajectory. Moreover, it increases the robustness of the system.

Item URL in elib:https://elib.dlr.de/116969/
Document Type:Conference or Workshop Item (Speech, Poster)
Title:Uncertainty Model for Template Feature Matching
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Zhang, HongmouHongmou.Zhang (at) dlr.dehttps://orcid.org/0000-0001-8284-5119
Grießbach, Denisdenis.griessbach (at) dlr.deUNSPECIFIED
Wohlfeil, Jürgenjuergen.wohlfeil (at) dlr.dehttps://orcid.org/0000-0003-1786-6460
Börner, Ankoanko.boerner (at) dlr.deUNSPECIFIED
Date:22 November 2017
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:In Press
Keywords:Uncertainty model, Image noise model, Template matching, Propagation of uncertainty, Sub-pixel matching
Event Title:The Pacific-Rim Symposium on Image and Video Technology 2017
Event Location:Wuhan, China
Event Type:international Conference
Event Dates:20-24 Nov 2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Optische Technologien und Anwendungen
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:31 Jul 2019 20:14

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