Mapping the Evolution of Hand Gesture Recognition: Techniques, Challenges and Innovations
Author(s):
Rameesa A.B, Bismin V Sherif
Keywords:
Hand Gesture Recognition, Convolution Neural Networks, Machine Learning, MediaPipe.
Abstract
Hand gesture recognition (HGR) has emerged as a vital component in human-computer interaction (HCI) systems, enabling natural and intuitive communication between humans and machines. It has many applications in virtual environment control and sign language translation, robot control, or music creation. This survey paper provides a comprehensive overview of the various techniques, methodologies, and advancements in the field of HGR. This research focuses on the development of an efficient hand gesture recognition system leveraging machine learning algorithms. The primary objective is to interpret and classify hand movements captured by sensors, transforming them into actionable commands.
Article Details
Unique Paper ID: 164731

Publication Volume & Issue: Volume 10, Issue 12

Page(s): 3041 - 3046
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