Home /Research /Deep-ChildAR bot
PERCEPTION

Deep-ChildAR bot

Yoon Jung Park, Hyocheol Ro, Tack‐Don Han

Year
2019
Citations
4

Abstract

We propose a projection-based augmented reality (AR) robot system that provides pervasive support for the education and safety of preschoolers via a deep learning framework. This system can utilize real-world objects as metaphors for educational tools by performing object detection based on deep learning in real-time, and it can help recognize the dangers of real-world objects that may pose risks to children. We designed the system in a simple and intuitive way to provide user-friendly interfaces and interactions for children. Children's experiences through the proposed system can improve their physical, cognitive, emotional, and thinking abilities.

Keywords

Computer scienceAugmented realityHuman–computer interactionObject (grammar)RobotCognitionDeep learningArtificial intelligenceObject detectionSimple (philosophy)

Related papers

Browse all PERCEPTION papers