engleski

Probabilistic Eye Contact Detection for the Robot- assisted ASD Diagnostic Protocol

This paper describes a probabilistic method for eye contact detection, aimed at facilitating the diagnostic process of Autism Spectrum Disorder (ASD). Eye contact, which is a special case of a wider social-attention cue called gaze, plays a major role in ASD diagnostics protocols used in clinical practice. Therefore, a reliable method for automatic eye contact detection is a key capability to open the way towards robot assisted autism diagnostics, which has the potential to reduce diagnostic time and increase reliability. The proposed method uses data from a simple low-resolution monocular camera, which is built into the NAO humanoid robot, and uses head pose and gaze direction as its inputs, which are very prone to outliers. We use a probabilistic framework in order to provide continuous measure of the eye contact and increase robustness to outliers. Furthermore, we take into account the temporal aspect of eye contact, in order to discard short glances which do not indicate actual transfer of attention. Initial experimental results, conducted in a laboratory setting, confirm that the proposed method can be effective in detecting eye contact with the NAO humanoid robot.

eye contact detection ; Autism Spectrum Disorder (ASD) ; diagnostics ; NAO humanoid robot

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