Deep Learning for Dynamic Hand Gesture Recognition: Applications, Challenges and Future Scope
Arpneek Kaur, Sandhya Bansal
Abstract
Hand Gesture Recognition is a very promising area of research over the last decade. It has found useful applications in touchless human-machine interaction in modern real-world problems. Dynamic Hand Gesture Recognition is an important requirement in most problems requiring recognition of moving gestures rather than a static pose. This review article provides a comprehensive survey of the recent deep learning-based systems. The articles have been selected by a systematic approach. We provide a detailed literature review and pictorial comparison of accuracies. The existing systems have been summarized concerning various aspects by using a tabular representation. From a study of the existing models, we find out the existing challenges, research gaps, and future scope in this direction.