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Vision-Based Joint Attention Detection for Autism Spectrum Disorders

  • Wanqi Zhang
  • , Zhiyong Wang
  • , Honghai Liu*
  • *Corresponding author for this work
  • Shanghai Jiao Tong University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Autism Spectrum Disorder (ASD) is one of the most common neurodevelopmental disorders in childhood. Its clinical symptoms mainly include narrow interests, stereotyped behavior and social communication disorders. There is still no cure for ASD. Only early detection and intervention can help to alleviate the symptoms and effects of ASD, so that ASD patients can adapt to the society and live a relatively normal life. Joint Attention is one of the core features of ASD and one of the key diagnostic indicators. In this paper, a detection test for Joint Attention is carried out among 8 non-ASD adults through a visual system which contains of one RGB camera and one Kinect. The result shows that the system can effectively detect the Joint Attention and has good accuracy.

Original languageEnglish
Title of host publicationCognitive Systems and Signal Processing - 4th International Conference, ICCSIP 2018, Revised Selected Papers
EditorsFuchun Sun, Dewen Hu, Huaping Liu
PublisherSpringer Verlag
Pages26-36
Number of pages11
ISBN (Print)9789811379826
DOIs
StatePublished - 2019
Externally publishedYes
Event4th International Conference on Cognitive Systems and Information Processing, ICCSIP 2018 - Beijing, China
Duration: 29 Nov 20181 Dec 2018

Publication series

NameCommunications in Computer and Information Science
Volume1005
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference4th International Conference on Cognitive Systems and Information Processing, ICCSIP 2018
Country/TerritoryChina
CityBeijing
Period29/11/181/12/18

Keywords

  • Autism Spectrum Disorder
  • Joint Attention
  • Visual system

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