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Person Identification System in a Platform for Enabling Interaction With Individuals Affected by Profound and Multiple Learning Disabilities
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Author(s): Carmen Campomanes-Alvarez (CTIC Technology Centre, Gijón – Asturias, Spain), Blanca Rosario Campomanes-Alvarez (CTIC Technology Centre, Gijón – Asturias, Spain) and Pelayo Quirós (CTIC Technology Centre, Gijón – Asturias, Spain)
Copyright: 2020
Volume: 12
Issue: 1
Pages: 17
Source title:
International Journal of Software Science and Computational Intelligence (IJSSCI)
Editor(s)-in-Chief: Brij Gupta (National Institute of Technology, Kurukshetra, India) and Andrew W.H. Ip (University of Saskatchewan, Canada)
DOI: 10.4018/IJSSCI.2020010103
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Abstract
Individuals with profound and multiple learning disabilities have restricted mobility together with sensory and intellectual impairments. They are unable to produce conventional behaviors to communicate particular needs. Within the INSENSION project, an intelligent platform for enabling the interaction of this kind of people with others, is developed. Its goal is to increase their ability of self-communication through digital services enhancing their well-being. The system will recognize facial expressions, body gestures, vocalizations, and physiological parameters using the information captured by cameras and sensors, and it will associate them with their meaning in an individualized way. Hence, person identification is required in order to personalize the understanding. In this work, a new facial recognition method is developed and configured to be included in the INSENSION platform. The proposed system identifies six individuals as well as discards the other people that could appear in the videos, assuring the monitoring of the right person.
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