DocumentCode :
652822
Title :
Towards Automated Full Body Detection of Laughter Driven by Human Expert Annotation
Author :
Mancini, Matteo ; Hofmann, Jurgen ; Platt, Tracey ; Volpe, Gualtiero ; Varni, Giovanna ; Glowinski, Donald ; Ruch, Willibald ; Camurri, A.
Author_Institution :
InfoMus Lab., Univ. of Genoa, Genoa, Italy
fYear :
2013
fDate :
2-5 Sept. 2013
Firstpage :
757
Lastpage :
762
Abstract :
Within the EU ILHAIRE Project, researchers of several disciplines (e.g., computer sciences, psychology) collaborate to investigate the psychological foundations of laughter, and to bring this knowledge into shape for the use in new technologies (i.e., affective computing). Within this framework, in order to endow machines with laughter capabilities (encoding as well as decoding), one crucial task is an adequate description of laughter in terms of morphology. In this paper we present a work methodology towards automated full body laughter detection: starting from expert annotations of laughter videos we aim to identify the body features that characterize laughter.
Keywords :
behavioural sciences computing; object detection; video signal processing; EU ILHAIRE Project; automated full body laughter detection; body features; human expert annotation; laughter capabilities; laughter videos; psychological foundations; Decoding; Encoding; Face; Feature extraction; Games; Psychology; Videos; analysis; annotation; automated; body; expressive; features; laughter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on
Conference_Location :
Geneva
ISSN :
2156-8103
Type :
conf
DOI :
10.1109/ACII.2013.140
Filename :
6681532
Link To Document :
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