Computational assessment of facial expression production in ASD children

Leo, Marco; Carcagnì, Pierluigi; Distante, Cosimo; Spagnolo, Paolo; Mazzeo, Pier Luigi; Rosato, Anna Chiara; Petrocchi, Serena; Pellegrino, Chiara; Levante, Annalisa; De Lumè, Filomena; Lecciso, Flavia

doi:10.3390/s18113993

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Journal article

Computational assessment of facial expression production in ASD children

Leo, Marco Institute of Applied Sciences and Intelligent Systems, National Research Council of Italy, via Monteroni, 73100 Lecce, Italy
Carcagnì, Pierluigi Institute of Applied Sciences and Intelligent Systems, National Research Council of Italy, via Monteroni, 73100 Lecce, Italy
Distante, Cosimo Institute of Applied Sciences and Intelligent Systems, National Research Council of Italy, via Monteroni, 73100 Lecce, Italy
Spagnolo, Paolo Institute of Applied Sciences and Intelligent Systems, National Research Council of Italy, via Monteroni, 73100 Lecce, Italy
Mazzeo, Pier Luigi Institute of Applied Sciences and Intelligent Systems, National Research Council of Italy, via Monteroni, 73100 Lecce, Italy
Rosato, Anna Chiara Amici di Nico Onlus, Via Campania, 6, 73046 Lecce, Italy
Petrocchi, Serena Institute of Communication and Health (ICH), Facoltà di scienze della comunicazione, Università della Svizzera italiana, Svizzera
Pellegrino, Chiara L’Adelfia Onlus, via S. Sangiovanni, 115-73031 Lecce, Italy
Levante, Annalisa Dipartimento di Storia, University of Salento, Società e Studi Sull’ Uomo, Studium 2000-Edificio 5-Via di Valesio, 73100 Lecce, Italy
De Lumè, Filomena Dipartimento di Storia, University of Salento, Società e Studi Sull’ Uomo, Studium 2000-Edificio 5-Via di Valesio, 73100 Lecce, Italy
Lecciso, Flavia Dipartimento di Storia, University of Salento, Società e Studi Sull’ Uomo, Studium 2000-Edificio 5-Via di Valesio, 73100 Lecce, Italy

16.11.2018

Published in:

Sensors. - 2018, vol. 18, no. 11, p. 3993

Quantitative facial expression analysis

Geometrical and temporal regularization of facial action units

ASD diagnosis and assessment

English In this paper, a computational approach is proposed and put into practice to assess the capability of children having had diagnosed Autism Spectrum Disorders (ASD) to produce facial expressions. The proposed approach is based on computer vision components working on sequence of images acquired by an off-the-shelf camera in unconstrained conditions. Action unit intensities are estimated by analyzing local appearance and then both temporal and geometrical relationships, learned by Convolutional Neural Networks, are exploited to regularize gathered estimates. To cope with stereotyped movements and to highlight even subtle voluntary movements of facial muscles, a personalized and contextual statistical modeling of non-emotional face is formulated and used as a reference. Experimental results demonstrate how the proposed pipeline can improve the analysis of facial expressions produced by ASD children. A comparison of system’s outputs with the evaluations performed by psychologists, on the same group of ASD children, makes evident how the performed quantitative analysis of children’s abilities helps to go beyond the traditional qualitative ASD assessment/diagnosis protocols, whose outcomes are affected by human limitations in observing and understanding multi-cues behaviors such as facial expressions.

Language

English

Classification

Medicine

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License undefined

Identifiers

RERO DOC 328296
DOI 10.3390/s18113993
ARK ark:/12658/srd1318990

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https://n2t.net/ark:/12658/srd1318990

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