Giving historical photographs a new perspective: introducing camera orientation parameters as new metadata in a large-scale 4D application

Please always quote using this URN: urn:nbn:de:bvb:20-opus-311103
  • The ongoing digitization of historical photographs in archives allows investigating the quality, quantity, and distribution of these images. However, the exact interior and exterior camera orientations of these photographs are usually lost during the digitization process. The proposed method uses content-based image retrieval (CBIR) to filter exterior images of single buildings in combination with metadata information. The retrieved photographs are automatically processed in an adapted structure-from-motion (SfM) pipeline to determine theThe ongoing digitization of historical photographs in archives allows investigating the quality, quantity, and distribution of these images. However, the exact interior and exterior camera orientations of these photographs are usually lost during the digitization process. The proposed method uses content-based image retrieval (CBIR) to filter exterior images of single buildings in combination with metadata information. The retrieved photographs are automatically processed in an adapted structure-from-motion (SfM) pipeline to determine the camera parameters. In an interactive georeferencing process, the calculated camera positions are transferred into a global coordinate system. As all image and camera data are efficiently stored in the proposed 4D database, they can be conveniently accessed afterward to georeference newly digitized images by using photogrammetric triangulation and spatial resection. The results show that the CBIR and the subsequent SfM are robust methods for various kinds of buildings and different quantity of data. The absolute accuracy of the camera positions after georeferencing lies in the range of a few meters likely introduced by the inaccurate LOD2 models used for transformation. The proposed photogrammetric method, the database structure, and the 4D visualization interface enable adding historical urban photographs and 3D models from other locations.show moreshow less

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Metadaten
Author: Ferdinand Maiwald, Jonas Bruschke, Danilo Schneider, Markus Wacker, Florian Niebling
URN:urn:nbn:de:bvb:20-opus-311103
Document Type:Journal article
Faculties:Fakultät für Mathematik und Informatik / Institut für Informatik
Language:English
Parent Title (English):Remote Sensing
ISSN:2072-4292
Year of Completion:2023
Volume:15
Issue:7
Article Number:1879
Source:Remote Sensing (2023) 15:7, 1879. https://doi.org/10.3390/rs15071879
DOI:https://doi.org/10.3390/rs15071879
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Tag:4D-GIS; Structure-from-Motion; camera orientation; content-based image retrieval; feature matching; historical images
Release Date:2024/02/07
Date of first Publication:2023/03/31
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International