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