Advanced Techniques for Geospatial Referencing in Online Media Repositories

Dominik Warch, Patrick Stellbauer and Pascal Neis ()
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Dominik Warch: Department of Applied Informatics and Geodesy, School of Technology, Mainz University of Applied Sciences, 55128 Mainz, Germany
Patrick Stellbauer: Department of Applied Informatics and Geodesy, School of Technology, Mainz University of Applied Sciences, 55128 Mainz, Germany
Pascal Neis: Department of Applied Informatics and Geodesy, School of Technology, Mainz University of Applied Sciences, 55128 Mainz, Germany

Future Internet, 2024, vol. 16, issue 3, 1-15

Abstract: In the digital transformation era, video media libraries’ untapped potential is immense, restricted primarily by their non-machine-readable nature and basic search functionalities limited to standard metadata. This study presents a novel multimodal methodology that utilizes advances in artificial intelligence, including neural networks, computer vision, and natural language processing, to extract and geocode geospatial references from videos. Leveraging the geospatial information from videos enables semantic searches, enhances search relevance, and allows for targeted advertising, particularly on mobile platforms. The methodology involves a comprehensive process, including data acquisition from ARD Mediathek, image and text analysis using advanced machine learning models, and audio and subtitle processing with state-of-the-art linguistic models. Despite challenges like model interpretability and the complexity of geospatial data extraction, this study’s findings indicate significant potential for advancing the precision of spatial data analysis within video content, promising to enrich media libraries with more navigable, contextually rich content. This advancement has implications for user engagement, targeted services, and broader urban planning and cultural heritage applications.

Keywords: natural language processing; named entity recognition; geocoding; online media repository; geospatial information extraction; image-to-text; audio-to-text (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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