Research Area:  Machine Learning

Abstract:

Hearing-impaired people can interact with other people through sign language. The proposed system tears down the communication barrier between Hard of hearing (HoH) community and those who do not know their sign language. In this paper, we have developed an algorithm to detect and segment the hand region from a depth image using the Microsoft Kinect sensor. The proposed algorithm works well in the cluttered environment, e.g. skin color background and hand overlaps the face. Convolution Neural networks (CNN) are applied to automatically construct features from Indian sign language (ISL) signs. These features are invariant to rotation and scaling. The proposed system recognizes gestures accurately up to 99.3%.

Keywords:  
Convolution neural network (CNN)
Hard of hearing (HoH)
Indian sign language (ISL)
Microsoft Kinect sensor

Author(s) Name:  Jayesh Gangrade, Jyoti Bharti

Publisher name:  Taylor and Francis

DOI:  10.1080/03772063.2020.1838342

Volume Information:  

Paper Link:   https://www.tandfonline.com/doi/abs/10.1080/03772063.2020.1838342