9th International Conference on ICT for Sustainable Development

Authors - Prem Shah, Mansi Patel, Himani Shah, Preet Patel, Sachi Joshi, Mohini Darji, Upesh Patel, Adey Purohit
Abstract - The aim of this paper is to delve into an important aspect of HCI (human-computer interaction) to become familiar with different techniques used in hand-gesture recognition. Hand gestures are nonverbal forms of communication in which information, emotions, or messages are conveyed by hand movements and positions. They are a universal mode of communication that can be used to supplement or replace spoken language. The study also comprehensively examines all the algorithms and models, like convolutional neural networks (CNNs), Hidden Markov Model (HMM), Latent Dirichlet Allocation (LDA), Mean-shift, etc. We assess their strengths and weaknesses according to their hand gesture detection and recognition performance. The paper also explores past trends of this ever-growing technology. We have studied around 30 papers to evaluate different techniques used for hand gesture recognition to date. Hand-gesture recognition is so important for review as it is extensively used in many domains like the gaming industry, healthcare and has many more limitless opportunities.