Embodied edutainment experience in a museum: discovering glass-blowing gestures
Pages 288 - 291
Abstract
Current technological progress has provided innovative methods and tools for learning and discovering various aspects of manual professions. To valorize their artifacts and mostly the craft and know-how behind them, museums are more and more attracted by these innovative interactive technologies. In this paper, we present an interactive installation for embodied edutainment experience developed in the framework of the exhibition “savoir-verre” implemented at “Musée des Arts et Métiers” in Paris. This installation had a double goal: to augment and improve the entire museum visiting experience (entertainment) and at the same time to go deeper into craft discovery, to learn the basics of the expert postures/gestures (education). In front of the camera, that captured their motions, visitors were invited to imitate 3 gestures of an expert glass-blower and received real-time multimodal (visual and auditory) feedback, guiding the execution of the gestures. The quantitative analysis of user's motion data captured during the use of the installation highlights its positive effect on users’ engagement, on their spatial and temporal performance, confirming the initial hypothesis that the multimodal real-time feedback can contribute to a better understanding and assimilation of expert gestures in glass blowing.
References
[1]
Eva Hornecker and Jacob Buur. 2006. Getting a grip on tangible interaction. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2006).
[2]
Vasileios Komianos. 2022. Immersive applications in museums: An analysis of the use of XR Technologies and the provided functionality based on Systematic Literature Review. JOIV: International Journal on Informatics Visualization 6, 1 (2022), 60.
[3]
Milka Trajkova, A'aeshah Alhakamy, Francesco Cafaro, Rashmi Mallappa, and Sreekanth R. Kankara. 2020. Move your body: Engaging museum visitors with human-data interaction. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (2020).
[4]
Marie-Monique Schaper, Maria Santos, Laura Malinverni, Juan Zerbini Berro, and Narcis Pares. 2018. Learning about the past through situatedness, embodied exploration and digital augmentation of Cultural Heritage Sites. International Journal of Human-Computer Studies 114 (2018), 36–50.
[5]
Marilena Alivizatou-Barakou 2017. Intangible Cultural Heritage and new technologies: Challenges and opportunities for cultural preservation and development. Mixed Reality and Gamification for Cultural Heritage(2017), 129–158.
[6]
Peng Tan, Damian Hills, Yi Ji, and Kaiping Feng. 2020. Case study: Creating embodied interaction with learning intangible cultural heritage through webar. Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems (2020).
[7]
Anne Laure Carre 2022. Mixed-reality demonstration and training of glassblowing. Heritage 5, 1 (2022), 103–128.
[8]
Zhe Cao, Tomas Simon, Shih-En Wei, and Yaser Sheikh. 2017. Realtime multi-person 2D pose estimation using part affinity fields. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017), 7291–7299.
[9]
Brenda Elizabeth Olivas-Padilla, Alina Glushkova, and Sotiris Manitsaris. 2023. Motion capture benchmark of real industrial tasks and traditional crafts for Human Movement Analysis. IEEE Access 11 (2023), 40075–40092.
[10]
Alina Glushkova, Dimitris Makrygiannis, and Sotiris Manitsaris. 2023. Interactive sensorimotor guidance for learning motor skills of a glass blower. Culture and Computing (2023), 29–43.
[11]
Sotiris Manitsaris, Gavriela Senteri, Dimitrios Makrygiannis, and Alina Glushkova. 2020. Human movement representation on multivariate time series for recognition of professional gestures and forecasting their trajectories. (May 2020). Retrieved July 20, 2023 from https://doi.org/10.3389/frobt.2020.00080
[12]
Dhara A. Sharma, Mohamed Faisal Chevidikunnan, Fayaz Rahman Khan, and Riziq Allah Gaowgzeh. 2016. Effectiveness of knowledge of result and knowledge of performance in the learning of a skilled motor activity by healthy young adults. (May 2016). Retrieved July 20, 2023 from https://doi.org/10.1589/jpts.28.1482
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Published In
October 2023
434 pages
ISBN:9798400703218
DOI:10.1145/3610661
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Published: 09 October 2023
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