Biologically vs. logic inspired encoding of facial actions and emotions in video
File(s)
Published version
Author(s)
Valstar, MF
Pantic, M
Type
Conference Paper
Abstract
Automatic facial expression analysis is an important aspect of Human Machine Interaction as the face is an important communicative medium. We use our face to signal interest, disagreement, intentions or mood through subtle facial motions and expressions. Work on automatic facial expression analysis can roughly be divided into the recognition of prototypic facial expressions such as the six basic emotional states and the recognition of atomic facial muscle actions (Action Units, AUs). Detection of AUs rather than emotions makes facial expression detection independent of culture-dependent interpretation, reduces the dimensonality of the problem and reduces the amount of training data required. Classic psychological studies suggest that humans consciously map AUs onto the basic emotion categories using a finite number of rules. On the other hand, recent studies suggest that humans recognize emotions unconsciously with a process that is perhaps best modeled by artificial neural networks (ANNs). This paper investigates these two claims. A comparison is made between detection of emotions directly from features vs a two-step approach where we first detect AUs and use the AUs as input to either a rulebase or an ANN to recognize emotions. The results suggest that the two-step approach is possible with a small loss of accuracy and that biologically inspired classification techniques outperfrom those that approach the classification problem from a logical perspective, suggesting that biologically inspired classifiers are more suitable for computer-based analysis of facial behaviour than logic inspired method;.
Date Issued
2006
Citation
2006, pp.325-328
ISBN
978-1-4244-0366-0
Publisher
IEEE
Source Title
IEEE International Conference on Multimedia and Expo (ICME 2006)
Conference
2006 IEEE International Conference on Multimedia and Expo - ICME 2006, Vols 1-5, Proceedings
Start Page
325
End Page
328
Copyright Statement
© 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Source
IEEE International Conference on Multimedia and Expo (ICME 2006)
Source Place
Toronto, CANADA