Abstract
Gesture recognition is topical in computer science and aims at interpreting human gestures via mathematical algorithms. Among the numerous applications are physical rehabilitation and imitation games. In this work, we suggest performing human gesture recognition within the context of a serious imitation game, which would aim at improving social interactions with teenagers with autism spectrum disorders. We use an artificial intelligence algorithm to detect the skeleton of the participant, then model the human pose space and describe an imitation learning method using a Gaussian Mixture Model in the Riemannian manifold.
Highlights
Autism spectrum disorders (ASD) are linked with brain development [1]
Gesture recognition is topical in computer science and aims at interpreting human gestures via mathematical algorithms
We suggest performing human gesture recognition within the context of a serious imitation game, which would aim at improving social interactions with teenagers with autism spectrum disorders
Summary
Autism spectrum disorders (ASD) are linked with brain development [1]. Main symptoms of ASD are difficulties with communication and social interactions, repetitive behaviors and obsessive interests.Autistic people have talent [2]. Autism spectrum disorders (ASD) are linked with brain development [1]. Main symptoms of ASD are difficulties with communication and social interactions, repetitive behaviors and obsessive interests. Autistic people have talent [2]. For instance: an exceptionally good memory, a great attention to detail, an excellent ability to respect schedules, and an exceptional level of honesty. Some of them are savants [3]. According to the World Health Organization [4], the global autism prevalence is around 1 in 160 children and autism is generally more common in boys than girls. Some autism prevalence studies were made per geographical area [5]
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