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spontaneous-facial-behavior
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A joint dictionary learning and regression model for intensity estimation of facial AUs
, Article Journal of Visual Communication and Image Representation ; Volume 47 , 2017 , Pages 1-9 ; 10473203 (ISSN) ; Fatemizadeh, E ; Mahoor, M. H ; Sharif University of Technology
Abstract
Automated intensity estimation of spontaneous Facial Action Units (AUs) defined by Facial Action Coding System (FACS) is a relatively new and challenging problem. This paper presents a joint supervised dictionary learning (SDL) and regression model for solving this problem. The model is casted as an optimization function consisting of two terms. The first term in the optimization concerns representing the facial images in a sparse domain using dictionary learning whereas the second term concerns estimating AU intensities using a linear regression model in the sparse domain. The regression model is designed in a way that considers disagreement between raters by a constant biasing factor in...
Intensity estimation of spontaneous facial action units based on their sparsity properties
, Article IEEE Transactions on Cybernetics ; Volume 46, Issue 3 , 2016 , Pages 817-826 ; 21682267 (ISSN) ; Fatemizadeh, E ; Mahoor, M. H ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2016
Abstract
Automatic measurement of spontaneous facial action units (AUs) defined by the facial action coding system (FACS) is a challenging problem. The recent FACS user manual defines 33 AUs to describe different facial activities and expressions. In spontaneous facial expressions, a subset of AUs are often occurred or activated at a time. Given this fact that AUs occurred sparsely over time, we propose a novel method to detect the absence and presence of AUs and estimate their intensity levels via sparse representation (SR). We use the robust principal component analysis to decompose expression from facial identity and then estimate the intensity of multiple AUs jointly using a regression model...