Computer vision tools for the non-invasive assessment of autism-related behavioral markers
Abstract
The early detection of developmental disorders is key to child outcome, allowing interventions
to be initiated that promote development and improve prognosis. Research on autism
spectrum disorder (ASD) suggests behavioral markers can be observed late in the first
year of life. Many of these studies involved extensive frame-by-frame video observation
and analysis of a child's natural behavior. Although non-intrusive, these methods
are extremely time-intensive and require a high level of observer training; thus,
they are impractical for clinical and large population research purposes. Diagnostic
measures for ASD are available for infants but are only accurate when used by specialists
experienced in early diagnosis. This work is a first milestone in a long-term multidisciplinary
project that aims at helping clinicians and general practitioners accomplish this
early detection/measurement task automatically. We focus on providing computer vision
tools to measure and identify ASD behavioral markers based on components of the Autism
Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure
three critical AOSI activities that assess visual attention. We augment these AOSI
activities with an additional test that analyzes asymmetrical patterns in unsupported
gait. The first set of algorithms involves assessing head motion by tracking facial
features, while the gait analysis relies on joint foreground segmentation and 2D body
pose estimation in video. We show results that provide insightful knowledge to augment
the clinician's behavioral observations obtained from real in-clinic assessments.
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https://hdl.handle.net/10161/9548Collections
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Guillermo Sapiro
James B. Duke Distinguished Professor of Electrical and Computer Engineering
Guillermo Sapiro received his B.Sc. (summa cum laude), M.Sc., and Ph.D. from the Department
of Electrical Engineering at the Technion, Israel Institute of Technology, in 1989,
1991, and 1993 respectively. After post-doctoral research at MIT, Dr. Sapiro became
Member of Technical Staff at the research facilities of HP Labs in Palo Alto, California.
He was with the Department of Electrical and Computer Engineering at the University
of Minnesota, where he held the position of Distinguished McKni

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