A dataset to test AI on forensic scenes

The aim of this article is to describe a dataset derived from crime scenes or fictitious accidents that can be used for artificial intelligence processing. The steps involved in setting up these forensic scenes, the data acquisition chain, classification and formatting will be described, as well as...

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Main Authors: H. Daudigny, P. Grussenmeyer
Format: Article
Language:English
Published: Copernicus Publications 2024-12-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://isprs-archives.copernicus.org/articles/XLVIII-2-W8-2024/117/2024/isprs-archives-XLVIII-2-W8-2024-117-2024.pdf
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author H. Daudigny
H. Daudigny
P. Grussenmeyer
author_facet H. Daudigny
H. Daudigny
P. Grussenmeyer
author_sort H. Daudigny
collection DOAJ
description The aim of this article is to describe a dataset derived from crime scenes or fictitious accidents that can be used for artificial intelligence processing. The steps involved in setting up these forensic scenes, the data acquisition chain, classification and formatting will be described, as well as the first tests carried out in artificial intelligence. The first data formatting operations will be carried out so that they can be integrated into machine learning and deep learning solutions; in particular the deep learning solution SuperPointTransformer (Robert et al., 2023). The difficulties linked to this type of work and the benefits of using artificial intelligence for forensic scenes will also be presented.
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series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
spelling doaj-art-838fdaea835f422e897903b222d37e972025-08-20T02:37:41ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342024-12-01XLVIII-2-W8-202411712310.5194/isprs-archives-XLVIII-2-W8-2024-117-2024A dataset to test AI on forensic scenesH. Daudigny0H. Daudigny1P. Grussenmeyer2Criminal School of Justice, University of Lausanne Civil, Batochime, 1015 Ecublens, SwitzerlandUniversité de Strasbourg, INSA Strasbourg, CNRS, ICube Laboratory UMR 7357, Photogrammetry and Geomatics Group, 67000 Strasbourg, FranceUniversité de Strasbourg, INSA Strasbourg, CNRS, ICube Laboratory UMR 7357, Photogrammetry and Geomatics Group, 67000 Strasbourg, FranceThe aim of this article is to describe a dataset derived from crime scenes or fictitious accidents that can be used for artificial intelligence processing. The steps involved in setting up these forensic scenes, the data acquisition chain, classification and formatting will be described, as well as the first tests carried out in artificial intelligence. The first data formatting operations will be carried out so that they can be integrated into machine learning and deep learning solutions; in particular the deep learning solution SuperPointTransformer (Robert et al., 2023). The difficulties linked to this type of work and the benefits of using artificial intelligence for forensic scenes will also be presented.https://isprs-archives.copernicus.org/articles/XLVIII-2-W8-2024/117/2024/isprs-archives-XLVIII-2-W8-2024-117-2024.pdf
spellingShingle H. Daudigny
H. Daudigny
P. Grussenmeyer
A dataset to test AI on forensic scenes
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title A dataset to test AI on forensic scenes
title_full A dataset to test AI on forensic scenes
title_fullStr A dataset to test AI on forensic scenes
title_full_unstemmed A dataset to test AI on forensic scenes
title_short A dataset to test AI on forensic scenes
title_sort dataset to test ai on forensic scenes
url https://isprs-archives.copernicus.org/articles/XLVIII-2-W8-2024/117/2024/isprs-archives-XLVIII-2-W8-2024-117-2024.pdf
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