Seminario Prof. Tsvi Kuflik: Automatic Detection of Social Behavior of Museum Visitor Pairs

Abstract: In many cases, visitors come to a museum in small groups. In these cases, the visitors’ social context has an impact on their museum visit experience. Knowing the social context may allow a system to provide socially-aware services to the visitors. Evidence of the social context can be gained from observing/monitoring the visitors’ social behavior. However, automatic identification of a social context requires on the one hand identifying typical social-behavior patterns, and on the other using relevant sensors that measure various signals and reason about them to detect the visitors’ social behavior. We present such typical social-behavior patterns of visitor pairs, identified by observations, and then, the instrumentation, detection process, reasoning, and analysis of measured signals that enables us to detect the visitors' social behavior. Simple sensors' data, such as proximity to other visitors, proximity to museum points-of-interest, and visitor orientation are used to detect social synchronization, attention to the social companion, and interest in museum exhibits. The presented approach may allow future research to offer adaptive services to museum visitors based on their social context, to support their group visit experience better.

https://www.uniba.it/it/ricerca/dipartimenti/informatica/notizie-eventi/eventi/seminario-prof.-tsvi-kuflik-automatic-detection-of-social-behavior-of-museum-visitor-pairs
Seminario Prof. Tsvi Kuflik: Automatic Detection of Social Behavior of Museum Visitor Pairs
2014-09-15T12:00:00+02:00
2014-09-15T14:00:00+02:00
Abstract: In many cases, visitors come to a museum in small groups. In these cases, the visitors’ social context has an impact on their museum visit experience. Knowing the social context may allow a system to provide socially-aware services to the visitors. Evidence of the social context can be gained from observing/monitoring the visitors’ social behavior. However, automatic identification of a social context requires on the one hand identifying typical social-behavior patterns, and on the other using relevant sensors that measure various signals and reason about them to detect the visitors’ social behavior. We present such typical social-behavior patterns of visitor pairs, identified by observations, and then, the instrumentation, detection process, reasoning, and analysis of measured signals that enables us to detect the visitors' social behavior. Simple sensors' data, such as proximity to other visitors, proximity to museum points-of-interest, and visitor orientation are used to detect social synchronization, attention to the social companion, and interest in museum exhibits. The presented approach may allow future research to offer adaptive services to museum visitors based on their social context, to support their group visit experience better.

Quando il 15/09/2014 dalle 12:00 alle 14:00 (Europe/Berlin / UTC200)
Dove Aula Gödel - Dipartimento di Informatica
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AVVISO DI SEMINARIO

Lunedì 15 Settembre ore 12.00, aula Gödel, Dipartimento di Informatica

Prof. Tsvi Kuflik, University of Haifa, Israel

Automatic Detection of Social Behavior of Museum Visitor Pairs

Abstract: In many cases, visitors come to a museum in small groups. In these cases, the visitors’ social context has an impact on their museum visit experience. Knowing the social context may allow a system to provide socially-aware services to the visitors. Evidence of the social context can be gained from observing/monitoring the visitors’ social behavior. However, automatic identification of a social context requires on the one hand identifying typical social-behavior patterns, and on the other using relevant sensors that measure various signals and reason about them to detect the visitors’ social behavior. We present such typical social-behavior patterns of visitor pairs, identified by observations, and then, the instrumentation, detection process, reasoning, and analysis of measured signals that enables us to detect the visitors' social behavior. Simple sensors' data, such as proximity to other visitors, proximity to museum points-of-interest, and visitor orientation are used to detect social synchronization, attention to the social companion, and interest in museum exhibits. The presented approach may allow future research to offer adaptive services to museum visitors based on their social context, to support their group visit experience better.

Tsvi Kuflik is associate Professor of Information Systems at the University of Haifa, where he leads a group that focuses on research on Ubiquitous User Modeling and on personalization and Intelligent User Interface for Cultural Heritage. Tsvi received his B.Sc. and M.Sc. in Computer Science and Ph.D. in Information Systems from Ben-Gurion University of the Negev. He has worked on personalization and intelligent user interfaces for cultural heritage over the past 10 years. During this period he spent a year in FBK/IRST in Trento and half a year at the University of Sydney working on these areas. Tsvi is an organizer of the Personal Access to Cultural Heritage (PATCH) workshop series. He has authored over a hundred and fifty technical papers and has edited several books.