Towards Interpreting Robotic System for Fingerspelling Recognition in Real Time

2018

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DOI 10.1145/3173386.3177085
Data confidence 70 medium
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Abstract

Hearing-impaired communities around the world communicate via a sign language. The focus of this work is to develop an interpreting human-robot interaction system that could act as a sign language interpreter in public places. This paper presents an ongoing work, which aims to recognize fingerspelling gestures in real time. To this end, we utilize a deep learning method for classification of 33 gestures used for fingerspelling by the local deaf-mute community.