The Efficiency of Sign Language Recognition using 3D Convolutional Neural Networks
Nantinee Soodtoetong, Eakbodin Gedkhaw · 2018
Sign language is a language that uses hand gesture to present a word within the hearing impairment communication. But, the important problem is sign language is not usual for ordinary people which is misunderstand meaningful. However, the advancement in computer vision and recognition process could be adapt in computer system to learn or recognize sign language. These are useful for the system to recognized and translated sign language which ordinary people understand. In this article presents a study in process and method which related with the recognition of sign language using deep learning. The algorithm is 3D-CNN used for recognized process and the images received from Kinect sensor. We found that the sign language recognition using 3D-CNN was effective, the highest accuracy of the recognition was 91.23%.