Hand Expression Aid Recognition (H.E.A.R)

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Hand Expression Aid Recognition (H.E.A.R)

Senior Design Showcase project, Wentworth Institute of Technology, College of Engineering and Computer Science, Department of Electrical and Computer Engineering, 2020

Dublin Core Metadata

title: Hand Expression Aid Recognition (H.E.A.R)

creator: Eternaty Cabeceiras, Alex Foilb and John Huynh

subject: American Sign Language, computer vision, Tensorflow, machine learning, Open CV

description: Hearing impairment hinders communication and activities of daily living. Methods to communicate between hearing- and hearing-impaired individuals usually place the burden of the activity upon the hearing-impaired individual. This project is developing a neural network that predicts the sign of American Sign Language (ASL) hand gestures into text. For initial development, images of ASL hand positions for letters are being used for machine learning toward classification. Such a method would assist with communication with no extra burden of activity placed on the hearing-impaired individual. This could be used by associates of hearing impaired or by staff of organizations that welcome hearing impaired individuals.

publisher: The Douglas D. Schumann Library and Learning Commons, Wentworth Institute of Technology

contributor:

date: 2020

type: Presentation

format: video recording

identifier:

source:

language: eng

relation:

coverage:

rights: https://rightsstatements.org/vocab/InC/1.0/

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