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A Computational Study of Expressive Facial Dynamics in Children with Autism
IEEE Transactions on Affective Computing ( IF 11.2 ) Pub Date : 2018-01-01 , DOI: 10.1109/taffc.2016.2578316
Tanaya Guha 1 , Zhaojun Yang 2 , Ruth B Grossman 3 , Shrikanth S Narayanan 2
Affiliation  

Several studies have established that facial expressions of children with autism are often perceived as atypical, awkward or less engaging by typical adult observers. Despite this clear deficit in the quality of facial expression production, very little is understood about its underlying mechanisms and characteristics. This paper takes a computational approach to studying details of facial expressions of children with high functioning autism (HFA). The objective is to uncover those characteristics of facial expressions, notably distinct from those in typically developing children, and which are otherwise difficult to detect by visual inspection. We use motion capture data obtained from subjects with HFA and typically developing subjects while they produced various facial expressions. This data is analyzed to investigate how the overall and local facial dynamics of children with HFA differ from their typically developing peers. Our major observations include reduced complexity in the dynamic facial behavior of the HFA group arising primarily from the eye region.

中文翻译:

自闭症儿童面部表情动力学的计算研究

几项研究已经确定,自闭症儿童的面部表情通常被典型的成人观察者认为是不典型的、笨拙的或不太吸引人的。尽管面部表情产生的质量存在明显缺陷,但对其潜在机制和特征知之甚少。本文采用计算方法来研究高功能自闭症 (HFA) 儿童面部表情的细节。目的是发现面部表情的那些特征,特别是不同于正常发育儿童的面部表情,否则难以通过目视检查发现。我们使用从患有 HFA 的受试者获得的动作捕捉数据,并且通常在他们产生各种面部表情时开发受试者。分析这些数据是为了调查 HFA 儿童的整体和局部面部动态与他们通常发育的同龄人有何不同。我们的主要观察结果包括主要来自眼部区域的 HFA 组动态面部行为的复杂性降低。
更新日期:2018-01-01
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