title: Automated prediction of preferences using facial expressions.
abstract: We introduce a computer vision problem from social cognition, namely, the automated detection of attitudes from a person's spontaneous facial expressions. To illustrate the challenges, we introduce two simple algorithms designed to predict observers' preferences between images (e.g., of celebrities) based on covert videos of the observers' faces. The two algorithms are almost as accurate as human judges performing the same task but nonetheless far from perfect. Our approach is to locate facial landmarks, then predict preference on the basis of their temporal dynamics. The database contains 768 videos involving four different kinds of preferences. We make it publically available.
authors: Estudis d'Informatica Multimedia i Telecomunicacions, Universitat Oberta de Catalunya, Barcelona, Spain ; Computer Vision Center, Universitat Autonoma de Barcelona, Barcelona, Spain.
authors: David
authors: D
authors: Masip
authors: Department of Psychology, Columbia University, New York, New York, United States of America.
authors: Michael S
authors: MS
authors: North
authors: Department of Psychology, Princeton University, Princeton, New Jersey, United States of America.
authors: Alexander
authors: A
authors: Todorov
authors: Department of Psychology, Princeton University, Princeton, New Jersey, United States of America.
authors: Daniel N
authors: DN
authors: Osherson
mesh_terms: D002755:Choice Behavior; D016001:Confidence Intervals; D005149:Facial Expression; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D060388:Support Vector Machine