<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bousmalis, K.</style></author><author><style face="normal" font="default" size="100%">Mehu, M.</style></author><author><style face="normal" font="default" size="100%">Pantic, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spotting agreement and disagreement: A survey of nonverbal audiovisual cues and tools</style></title><secondary-title><style face="normal" font="default" size="100%">3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, 2009 (ACII 2009)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">agreement</style></keyword><keyword><style  face="normal" font="default" size="100%">automatic analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">disagreement</style></keyword><keyword><style  face="normal" font="default" size="100%">social signal processing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/09/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5349477</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Amsterdam, The Netherlands</style></pub-location><isbn><style face="normal" font="default" size="100%">978-1-4244-4800-5</style></isbn><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;While detecting and interpreting temporal patterns of non-verbal behavioral cues in a given context is a natural and often unconscious process for humans, it remains a rather difficult task for computer systems. Nevertheless, it is an important one to achieve if the goal is to realise a naturalistic communication between humans and machines. Machines that are able to sense social attitudes like agreement and disagreement and respond to them in a meaningful way are likely to be welcomed by users due to the more natural, efficient and human-centered interaction they are bound to experience. This paper surveys the nonverbal cues that could be present during agreement and disagreement behavioural displays and lists a number of tools that could be useful in detecting them, as well as a few publicly available databases that could be used to train these tools for analysis of spontaneous, audiovisual instances of agreement and disagreement.&lt;/p&gt;
</style></abstract><accession-num><style face="normal" font="default" size="100%">11007592</style></accession-num></record></records></xml>