Real Time Sign Language Estimation System
Pushkar Kurhekar, Janvi Phadtare, Sourav Sinha, Kavita Pankaj Shirsat · 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI) · 2019
This paper presents a system which assists people with speech and hearing disabilities to communicate freely. The model is able to extract signs from videos, by processing the video frame by frame under minimally cluttered background. This sign is then presented in readable text. The system uses a Convolutional Neural Network (CNN) and fastai - a deep learning library, along with OpenCV for webcam input and displaying the predicted sign. Experimental results show decent segmentation of signs under different backgrounds and high accuracy in gesture recognition.