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Reflective Signs : digital signs that adapt to audience attention

Title data

Müller, Jörg ; Exeler, Juliane ; Buzeck, Markus ; Krüger, Antonio:
Reflective Signs : digital signs that adapt to audience attention.
In: Tokuda, Hideyuki ; Beigl, M. ; Friday, A. ; Brush, A. J. B. ; Tobe, Y. (ed.): Pervasive Computing. - Berlin ; Heidelberg : Springer , 2009 . - pp. 17-24 . - (Lecture Notes in Computer Science ; 5538 )
ISBN 978-3-642-01516-8
DOI: https://doi.org/10.1007/978-3-642-01516-8_3

Abstract in another language

This paper presents ReflectiveSigns, i.e. digital signage (public electronic displays) that automatically learns the audience preferences for certain content in different contexts and presents content accordingly. Initially, content (videos, images and news) are presented in a random manner. Using cameras installed on the signs, the system observes the audience and detects if someone is watching the content (via face detection). The anonymous view time duration is then stored in a central database, together with date, time and sign location. When scheduling content, the signs calculate the expected view time for each content type depending on sign location and time using a Naive Bayes classifier. Content is then selected randomly, with the probability for each content weighted by the expected view time. The system has been deployed for two months on four digital signs in a university setting using semi realistic content & content types. We present a first evaluation of this approach that concentrates on major effects and results from interviews with 15 users.

Further data

Item Type: Article in a book
Refereed: Yes
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science VIII > Chair Applied Computer Science VIII - Univ.-Prof. Dr. Jörg Müller
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science VIII
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works
Date Deposited: 15 Jan 2019 08:38
Last Modified: 15 Jan 2019 08:38
URI: https://eref.uni-bayreuth.de/id/eprint/42040