a r t i c l e i n f o Facial expression is central to human experience. Its efficiency and valid measurement are challenges that automated facial image analysis seeks to address. Most publically available databases are limited to 2D static images or video of posed facial behavior. Because posed and un-posed (aka " spontaneous ") facial expressions differ along several dimensions including compl...

In both biometrics and facial expression recognition, previous literature emphasizes the configuration of facial features instead of their dynamics. I propose that dynamics provide essential information about person identity, neural control, communicative intent, and interpersonal coordination. To investigate this hypothesis, my colleagues and I have used multiple methods, including perceptual ...

This paper discusses Integrated System for Facial Expression Recognition (ISFER), which performs facial expression analysis from a still dual facial view image. The system consists of three major parts: facial data generator, facial data evaluator and facial data analyser. While the facial data generator applies fairly conventional techniques for facial features extraction, the rest of the syst...

The automatic recognition of facial expression presents a significant challenge to the pattern analysis and man-machine interaction research community. In this paper, a novel system is proposed to recognize human facial expressions based on the expression sketch. Firstly, facial expression sketch is extracted by an GPU-based real-time edge detection and sharpening algorithm from original gray i...

ÐWe propose a method for automatically classifying facial images based on labeled elastic graph matching, a 2D Gabor wavelet representation, and linear discriminant analysis. Results of tests with three image sets are presented for the classification of sex, arace,o and expression. A visual interpretation of the discriminant vectors is provided. Index TermsÐComputer vision, face recognition, fa...

Facial expressions are formed through complicated muscular actions and can be taxonomized using the Facial Action Coding System (FACS). FACS breaks down human facial expressions into discreet action units (AUs) and often combines them together to form more elaborate expressions. In this paper, we present a comparative analysis of performance of automated facial expression recognition from therm...

This report details a procedure for generating a computational model of facial expressions. This is a growing and relatively new type of problem within computer vision. One of the fundamental problems when trying to develop a computational model of facial expression in previous approaches is the lack of a consistent method of measuring expression. This report solves this problem by the computat...

Most facial expression analysis systems attempt to recognize facial expressions from data collected in a highly controlled laboratory with very high resolution frontal faces (face regions greater than 200 x 200 pixels) and cannot handle large head motions. In real environments such as smart meetings, a facial expression analysis system must be able to automatically recognize expressions at lowe...

In this paper, we propose a novel approach for facial expression analysis and recognition. The main contributions of the paper are as follows. First, we propose a temporal recognition scheme that classifies a given image in an unseen video into one of the universal facial expression categories using an analysis–synthesis scheme. The proposed approach relies on tracked facial actions provided by...

Facial expression analysis has been well studied in recent years; however, these mainly focus on domains of posed or clear facial expressions. Meanwhile, subtle/micro-expressions are rarely analyzed, due to three main difficulties: inter-class similarity (hardly discriminate facial expressions of two subtle emotional states from a person), intra-class dissimilarity (different facial morphology ...