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Build Your Own Training Data -- Synthetic Data for Object Detection in Aerial Images

Laux, Lea and Schirmer, Sebastian and Schopferer, Simon and Dauer, Johann C. (2022) Build Your Own Training Data -- Synthetic Data for Object Detection in Aerial Images. 4th Workshop on Avionics Systems and Software Engineering, 2022-02-22, Virtuell.

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Abstract

Machine learning has become one of the most widely used techniques in artificial intelligence, especially for image processing. One of the biggest challenges in developing an accurate image processing model is to collect large amounts of data that are sufficiently close to the real-world scenario. Ideally, real-world data is therefore used for model training. Unfortunately, real-world data is often insufficiently available and expensive to generate. Therefore, models are trained using synthetic data. However, there is no standardized method of how training data is generated and which properties determine the data quality. In this paper, we present first steps towards the generation of large amounts of data for human detection based on aerial images. To create labeled aerial images, we are using Unreal Engine and AirSim. We report on first impressions of the generated labeled aerial images and identify future challenges-current simulation tools can be used to create realistic and diverse images including labeling, but native support would be beneficial to ease their usage.

Item URL in elib:https://elib.dlr.de/185409/
Document Type:Conference or Workshop Item (Speech)
Title:Build Your Own Training Data -- Synthetic Data for Object Detection in Aerial Images
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Laux, LeaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Schirmer, SebastianUNSPECIFIEDhttps://orcid.org/0000-0002-4596-2479UNSPECIFIED
Schopferer, SimonUNSPECIFIEDhttps://orcid.org/0000-0001-5254-3961UNSPECIFIED
Dauer, Johann C.UNSPECIFIEDhttps://orcid.org/0000-0002-8287-2376UNSPECIFIED
Date:22 February 2022
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Machine Learning, Synthetic Data, Simulation Environment, Unmanned Aircraft, Human Detection
Event Title:4th Workshop on Avionics Systems and Software Engineering
Event Location:Virtuell
Event Type:Workshop
Event Date:22 February 2022
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Components and Systems
DLR - Research area:Aeronautics
DLR - Program:L CS - Components and Systems
DLR - Research theme (Project):L - Unmanned Aerial Systems
Location: Braunschweig
Institutes and Institutions:Institute of Flight Systems > Unmanned Aircraft
Deposited By: Schirmer, Sebastian
Deposited On:24 Feb 2022 14:46
Last Modified:24 Apr 2024 20:46

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