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.
Towards automated full body detection of laughter driven by human expert annotation / Mancini, Maurizio; J., Hofmann; T., Platt; Volpe, Gualtiero; Varni, Giovanna; D., Glowinski; W., Ruch; Camurri, Antonio. - (2013), pp. 757-762. (Intervento presentato al convegno 5th Humaine Association Conference on Affective Computing and Intelligent Interaction, ACII 2013 tenutosi a Geneva, Switzerland) [10.1109/ACII.2013.140].
Towards automated full body detection of laughter driven by human expert annotation
MANCINI, MAURIZIO;VOLPE, GUALTIERO;
2013
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
