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Fusing tie points' RGB and thermal information for mapping large areas based on aerial images: A study of fusion performance under different flight configurations and experimental conditions

Hou, Yu; Volk, Rebekka ORCID iD icon 1; Chen, Meida; Soibelman, Lucio
1 Institut für Industriebetriebslehre und Industrielle Produktion (IIP), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Three-dimensional thermal mapping from aerial images can be used in energy audits. Tie points that define the location of object points in a 3D space for reconstructing a 3D model, also include thermal information, which plays an important role in energy audits. However, it is often harder and less accurate to extract common features and determine tie points from low-resolution thermal images. It is more effective and accurate to use high-definition RGB images to determine tie points and fuse the RGB and thermal information. In this study, we investigate how to utilize high-definition RGB images that allow for more accurate tie point detection, how different flight configurations affect tie point data fusion, and how tie point data fusion performance can be improved. We propose a tie points' thermal and RGB data-fusion framework to create district-level thermal mapping to solve such problems. This paper aims to evaluate how different flight configurations affect the results of the proposed data fusion approach. Flight configurations include different camera altitudes (60 m and 35 m), distinct camera angles (45 degrees and 30 degrees), diverse flight path designs (mesh grid and Y path), and various building styles (campus buildings and city buildings).
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Postprint §
DOI: 10.5445/IR/1000129014
Veröffentlicht am 28.01.2022
DOI: 10.1016/j.autcon.2021.103554
Zitationen: 26
Zitationen: 26
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Industriebetriebslehre und Industrielle Produktion (IIP)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 04.2021
Sprache Englisch
Identifikator ISSN: 0926-5805
KITopen-ID: 1000129014
Erschienen in Automation in construction
Verlag Elsevier
Band 124
Seiten Art.-Nr.: 103554
Vorab online veröffentlicht am 27.01.2021
Schlagwörter Thermal mapping; Large scale photogrammetry; Tie points; Data fusion; UAS data collection
Nachgewiesen in Scopus
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