[article] 
inResearch in Autism Spectrum Disorders > 65 (September 2019) . - p.14-24

Titre :	A pilot study to identify autism related traits in spontaneous facial actions using computer vision
Type de document :	Texte imprimé et/ou numérique
Auteurs :	Manar D. SAMAD, Auteur ; Norou DIAWARA, Auteur ; Jonna L. BOBZIEN, Auteur ; Cora M. TAYLOR, Auteur ; John W. HARRINGTON, Auteur ; Khan M. IFTEKHARUDDIN, Auteur
Article en page(s) :	p.14-24
Langues :	Anglais (eng)
Mots-clés :	ASD  Behavioral marker  Differential traits  Facial action units  Computer vision  Spontaneous expressions
Index. décimale :	PER Périodiques
Résumé :	Background Individuals with autism spectrum disorders (ASD) may be differentiated from typically developing controls (TDC) based on phenotypic features in spontaneous facial expressions. Computer vision technology can automatically track subtle facial actions to gain quantitative insights into ASD related behavioral abnormalities. Method This study proposes a novel psychovisual human-study to elicit spontaneous facial expressions in response to a variety of social and emotional contexts. We introduce a markerless facial motion capture and computer vision methods to track spontaneous and subtle activations of facial muscles. The facial muscle activations are encoded into ten representative facial action units (FAU) to gain quantitative, granular, and contextual insights into the psychophysical development of the participating individuals. Statistical tests are performed to identify differential traits in individuals with ASD after comparing those in a cohort of age-matched TDC individuals. Results The proposed framework has revealed significant difference (p?
En ligne :	https://doi.org/10.1016/j.rasd.2019.05.001
Permalink :	https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=401

[article] A pilot study to identify autism related traits in spontaneous facial actions using computer vision [Texte imprimé et/ou numérique] / Manar D. SAMAD, Auteur ; Norou DIAWARA, Auteur ; Jonna L. BOBZIEN, Auteur ; Cora M. TAYLOR, Auteur ; John W. HARRINGTON, Auteur ; Khan M. IFTEKHARUDDIN, Auteur . - p.14-24.
Langues : Anglais (eng)
in Research in Autism Spectrum Disorders > 65 (September 2019) . - p.14-24

Mots-clés :	ASD  Behavioral marker  Differential traits  Facial action units  Computer vision  Spontaneous expressions
Index. décimale :	PER Périodiques
Résumé :	Background Individuals with autism spectrum disorders (ASD) may be differentiated from typically developing controls (TDC) based on phenotypic features in spontaneous facial expressions. Computer vision technology can automatically track subtle facial actions to gain quantitative insights into ASD related behavioral abnormalities. Method This study proposes a novel psychovisual human-study to elicit spontaneous facial expressions in response to a variety of social and emotional contexts. We introduce a markerless facial motion capture and computer vision methods to track spontaneous and subtle activations of facial muscles. The facial muscle activations are encoded into ten representative facial action units (FAU) to gain quantitative, granular, and contextual insights into the psychophysical development of the participating individuals. Statistical tests are performed to identify differential traits in individuals with ASD after comparing those in a cohort of age-matched TDC individuals. Results The proposed framework has revealed significant difference (p?
En ligne :	https://doi.org/10.1016/j.rasd.2019.05.001
Permalink :	https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=401