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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...
Compressive sensing for elliptic localization in MIMO radars
, Article 24th Iranian Conference on Electrical Engineering, 10 May 2016 through 12 May 2016 ; 2016 , Pages 525-528 ; 9781467387897 (ISBN) ; Amiri, R ; Behnia, F ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
Abstract
In this paper, a sparsity-aware target localization method in multiple-input-multiple-output (MIMO) radars by utilizing time difference of arrival (TDOA) measurements is proposed. This method provides a maximum likelihood (ML) estimator for target position by employing compressive sensing techniques. Also, for fast convergence and mitigating the mismatch problem due to grid discretization, we address a block-based search coupled with an adaptive dictionary learning technique. The Cramer-Rao lower bound for this model is derived as a benchmark. Simulations results are included to verify the localization performance