<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dragos Datcu</style></author><author><style face="normal" font="default" size="100%">Mirela Popa</style></author><author><style face="normal" font="default" size="100%">L.J.M. Rothkrantz</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Automatic recognition of drivers affect using face analysis</style></title><secondary-title><style face="normal" font="default" size="100%">Driver Car Interaction &amp; Interface 2009</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">face analysis and 3D Active Appearance Model and facial expressions</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">nov</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Praag and Czech Republic</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The emotion state of car drivers has a direct influence on the style of driving and especially on the attentiveness and degree of risk drivers take while driving. In this paper we present the results of our research in automatic recognition of affect state of the drivers based on video analysis of faces. The approach makes use of Viola&amp;Jones face detection and Active Appearance Models for face shape and texture extraction and Adaboost.M2 for recognition of drivers' affects. The novelty of the work consists of a new algorithm for 3D video face analysis. AAM is used to extract visual features such as appearance-related parameters. These are further on used both ways first to detect facial expressions and second to compute the gaze. The facial expressions and gaze provide indications for the psychological profile of the driver given the level of responsiveness and perceptiveness in specific situations on the road.</style></abstract></record></records></xml>