Affective intelligence: The human face of ai

Malatesta, L; Karpouzis, K; Raouzaiou, A

dc.contributor.author	Malatesta, L	en
dc.contributor.author	Karpouzis, K	en
dc.contributor.author	Raouzaiou, A	en
dc.date.accessioned	2014-03-01T02:45:57Z
dc.date.available	2014-03-01T02:45:57Z
dc.date.issued	2009	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32474
dc.subject	Affective Computing	en
dc.subject	Behavioral Science	en
dc.subject	Computer Model	en
dc.subject	Computer Vision	en
dc.subject	Human Computer Interaction	en
dc.subject	Machine Learning	en
dc.subject	Representation Theory	en
dc.subject	Research and Development	en
dc.subject	Signal Processing	en
dc.subject.other	Affective Computing	en
dc.subject.other	Behavioral science	en
dc.subject.other	Computational model	en
dc.subject.other	Diverse fields	en
dc.subject.other	Human faces	en
dc.subject.other	Human-centric	en
dc.subject.other	Human-computer interaction system	en
dc.subject.other	Input signal	en
dc.subject.other	Machine learning techniques	en
dc.subject.other	Machine-learning	en
dc.subject.other	Processing power	en
dc.subject.other	Representation model	en
dc.subject.other	Representation theory	en
dc.subject.other	Research and development	en
dc.subject.other	Research initiatives	en
dc.subject.other	Artificial intelligence	en
dc.subject.other	Behavioral research	en
dc.subject.other	Computer vision	en
dc.subject.other	Industrial research	en
dc.subject.other	Knowledge management	en
dc.subject.other	Learning algorithms	en
dc.subject.other	Machine design	en
dc.subject.other	Robot learning	en
dc.subject.other	Signal processing	en
dc.subject.other	Human computer interaction	en
dc.title	Affective intelligence: The human face of ai	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-642-03226-4_4	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-642-03226-4_4	en
heal.publicationDate	2009	en
heal.abstract	Affective computing has been an extremely active research and development area for some years now, with some of the early results already starting to be integrated in human-computer interaction systems. Driven mainly by research initiatives in Europe, USA and Japan and accelerated by the abundance of processing power and low-cost, unintrusive sensors like cameras and microphones, affective computing functions in an interdisciplinary fashion, sharing concepts from diverse fields, such as signal processing and computer vision, psychology and behavioral sciences, human-computer interaction and design, machine learning, and so on. In order to form relations between low-level input signals and features to high-level concepts such as emotions or moods, one needs to take into account the multitude of psychology and representation theories and research findings related to them and deploy machine learning techniques to actually form computational models of those. This chapter elaborates on the concepts related to affective computing, how these can be connected to measurable features via representation models and how they can be integrated into human-centric applications. © 2009 Springer Berlin Heidelberg.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-642-03226-4_4	en
dc.identifier.volume	5640 LNAI	en
dc.identifier.spage	53	en
dc.identifier.epage	70	en