dc.contributor.author | Ceccarelli, Sofia | en_US |
dc.contributor.author | Cesta, Amedeo | en_US |
dc.contributor.author | Cortellessa, Gabriella | en_US |
dc.contributor.author | Benedictis, Riccardo De | en_US |
dc.contributor.author | Fracasso, Francesca | en_US |
dc.contributor.author | Leopardi, Laura | en_US |
dc.contributor.author | Ligios, Luca | en_US |
dc.contributor.author | Lombardi, Ernesto | en_US |
dc.contributor.author | Malatesta, Saverio Giulio | en_US |
dc.contributor.author | Oddi, Angelo | en_US |
dc.contributor.author | Pagano, Alfonsina | en_US |
dc.contributor.author | Palombini, Augusto | en_US |
dc.contributor.author | Romagna, Gianmauro | en_US |
dc.contributor.author | Sanzari, Marta | en_US |
dc.contributor.author | Schaerf, Marco | en_US |
dc.contributor.editor | Bucciero, Alberto | en_US |
dc.contributor.editor | Fanini, Bruno | en_US |
dc.contributor.editor | Graf, Holger | en_US |
dc.contributor.editor | Pescarin, Sofia | en_US |
dc.contributor.editor | Rizvic, Selma | en_US |
dc.date.accessioned | 2023-09-02T07:44:44Z | |
dc.date.available | 2023-09-02T07:44:44Z | |
dc.date.issued | 2023 | |
dc.identifier.isbn | 978-3-03868-217-2 | |
dc.identifier.issn | 2312-6124 | |
dc.identifier.uri | https://doi.org/10.2312/gch.20231177 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/gch20231177 | |
dc.description.abstract | Analysing visitors' behaviour in museums and cultural sites is a key element to manage spaces and artworks arrangement. Museum stakeholders and curators may benefit from technology to improve the visit experience. This paper presents the preliminary results of the ARTEMISIA project, which aims to exploit Artificial Intelligence (AI) techniques to study, design and develop a methodology to interpret visitors' behaviour within a museum context. The Museum of Rome (Italy) Palazzo Braschi was selected for the project's first stage. The objective is to combine existing research with analytical techniques using data acquired from new generation stereo cameras (users' stand-still positions, viewpoint direction, movements) and other biases commonly used in the retail market (users' flow towards corridors, level of attention, etc). Mapping, and further predicting, users' patterns in regard to the museum arrangement may help to suggest changes in the space (new indications, updated storytelling or changes in thematic configuration). AI algorithms analyse data gathered from motion sensors in order to obtain a grid of references of all criteria related to users' experience (UX) and the effect of a museum visit on them, identifying new forms of visitors profiling and leading to the development of customised applications in public and private contexts. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.rights | Attribution 4.0 International License | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.subject | CCS Concepts: Computing methodologies → Artificial Intelligence; Computer Vision; Interest point and salient region detection | |
dc.subject | Computing methodologies → Artificial Intelligence | |
dc.subject | Computer Vision | |
dc.subject | Interest point and salient region detection | |
dc.title | Artificial Intelligence Algorithms for the Analysis of User Experience in Palazzo Braschi Museum | en_US |
dc.description.seriesinformation | Eurographics Workshop on Graphics and Cultural Heritage | |
dc.description.sectionheaders | Posters and Demos | |
dc.identifier.doi | 10.2312/gch.20231177 | |
dc.identifier.pages | 185-187 | |
dc.identifier.pages | 3 pages | |