Paper Info
Title
Towards Automated Full Body Detection of Laughter Driven by Human Expert Annotation
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.
Year
DOI
Venue
2013
10.1109/ACII.2013.140
ACII
Keywords
Field
DocType
video signal processing,body,laughter video,adequate description,crucial task,laughter,laughter videos,features,laughter driven,expressive,automated,eu ilhaire project,human expert annotation,annotation,expert annotation,laughter capabilities,psychological foundations,towards automated full body,analysis,behavioural sciences computing,object detection,affective computing,computer science,automated full body laughter detection,body features,new technology,automated full body laughter,laughter capability
Laughter,Object detection,Annotation,Communication,Computer science,Emerging technologies,Affective computing,Encoding (memory)
Conference
ISSN
Citations 
PageRank 
2156-8103
4
0.47
References 
Authors
6
8
Name
Order
Citations
PageRank
Maurizio Mancini159755.25
Jennifer Hofmann2352.77
Tracey Platt3352.77
Gualtiero Volpe4864101.42
Giovanna Varni517026.42
Donald Glowinski613114.01
Willibald Ruch7183.76
Antonio Camurri81107142.92