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Automatic Schaeffer's gestures recognition system
Author(s) -
GomezDonoso Francisco,
Cazorla Miguel,
GarciaGarcia Alberto,
GarciaRodriguez Jose
Publication year - 2016
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/exsy.12160
Subject(s) - gesture , computer science , sign language , set (abstract data type) , gesture recognition , motion (physics) , rgb color model , sign (mathematics) , artificial intelligence , dynamic time warping , motion capture , cognition , human–computer interaction , computer vision , linguistics , psychology , programming language , mathematics , mathematical analysis , philosophy , neuroscience
Schaeffer's sign language consists of a reduced set of gestures designed to help children with autism or cognitive learning disabilities to develop adequate communication skills. Our automatic recognition system for Schaeffer's gesture language uses the information provided by an RGB‐D camera to capture body motion and recognize gestures using dynamic time warping combined with k‐nearest neighbors methods. The learning process is reinforced by the interaction with the proposed system that accelerates learning itself thus helping both children and educators. To demonstrate the validity of the system, a set of qualitative experiments with children were carried out. As a result, a system which is able to recognize a subset of 11 gestures of Schaeffer's sign language online was achieved.