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Classifying self-cast shadow regions in aerial camera images

Gatter, Alexander (2018) Classifying self-cast shadow regions in aerial camera images. In: 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2018. AVSS 2018, 27.-30. Nov. 2018, Auckland, Neuseeland.

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Abstract

In many fields of airborne surveillance, self-cast shadows (i.e. shadows in a scene which are cast by an aircraft) pose a not negligible problem for image processing tasks. Self-cast shadows can impede the stability of computer vision applications like remote sensing, visual odometry, or tracking tasks. In order to be able to reliably identify selfcast shadows in on-board camera images, a model-based approach has been developed. This approach utilizes easily accessible sensor data to make predictions about the position and the shape of self-cast shadows. The predicted shadow is then used to search for image regions which contain self-cast shadows. The developed approach is presented in detail in this paper. Further, the approach is applied on flight test data which has been recorded by a helicopter that is operated by the German Aerospace Center (DLR). The evaluation of the flight test shows that the approach is able to identify self-cast shadow regions with a high reliability.

Item URL in elib:https://elib.dlr.de/124781/
Document Type:Conference or Workshop Item (Poster)
Title:Classifying self-cast shadow regions in aerial camera images
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Gatter, AlexanderAlexander.Gatter (at) dlr.deUNSPECIFIED
Date:December 2018
Journal or Publication Title:2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2018
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Computer Vision; Shadow Detection; Optical Navigation; Classification; Image Segmentation
Event Title:AVSS 2018
Event Location:Auckland, Neuseeland
Event Type:international Conference
Event Dates:27.-30. Nov. 2018
Organizer:IEEE/AVSS
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:air traffic management and operations
DLR - Research area:Aeronautics
DLR - Program:L AO - Air Traffic Management and Operation
DLR - Research theme (Project):L - Human factors and safety in Aeronautics
Location: Braunschweig
Institutes and Institutions:Institute of Flight Systems > Rotorcraft
Deposited By: Gatter, Alexander
Deposited On:12 Dec 2018 16:11
Last Modified:12 Dec 2018 16:11

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