The MuseLearn Platform: Personalized Content for Museum Visitors Assisted by Vision-Based Recognition and 3D Pose Estimation of Exhibits - Artificial Intelligence Applications and Innovations Access content directly
Conference Papers Year : 2020

The MuseLearn Platform: Personalized Content for Museum Visitors Assisted by Vision-Based Recognition and 3D Pose Estimation of Exhibits

G. Styliaras
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C. Constantinopoulos
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P. Panteleris
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D. Michel
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N. Pantzou
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K. Papavasileiou
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Kali Tzortzi
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A. Argyros
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Dimitrios Kosmopoulos
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Abstract

MuseLearn is a platform that enhances the presentation of the exhibits of a museum with multimedia-rich content that is adapted and recommended for certain visitor profiles and playbacks on their mobile devices. The platform consists mainly of a content management system that stores and prepares multimedia material for the presentation of exhibits; a recommender system that monitors objectively the visitor’s behavior so that it can further adapt the content to their needs; and a pose estimation system that identifies an exhibit and links it to the additional content that is prepared for it. We present the systems and the initial results for a selected set of exhibits in Herakleidon Museum, a museum holding temporary exhibitions mainly about ancient Greek technology. The initial evaluation that we presented is encouraging for all systems. Thus, the plan is to use the developed systems for all museum exhibits as well as to enhance their functionality.
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hal-04050594 , version 1 (29-03-2023)

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G. Styliaras, C. Constantinopoulos, P. Panteleris, D. Michel, N. Pantzou, et al.. The MuseLearn Platform: Personalized Content for Museum Visitors Assisted by Vision-Based Recognition and 3D Pose Estimation of Exhibits. 16th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Jun 2020, Neos Marmaras, Greece. pp.439-451, ⟨10.1007/978-3-030-49161-1_37⟩. ⟨hal-04050594⟩
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