A Convolutional Neural Network Framework for Robust Hand Gesture Recognition

A Convolutional Neural Network Framework for Robust Hand Gesture Recognition
Author(s):
Rameesa A.B, Bismin V Sherif
Keywords:
Hand Gesture Recognition, Convolution Neural Network, k-Nearest Neighbors, Random Forest, SVM
Abstract
Hand gesture recognition has become increasingly relevant in enhancing human-computer interaction across various applications, from virtual reality to assistive technologies. This paper introduces a novel approach using Convolutional Neural Networks (CNNs) to accurately recognize hand gestures and uniquely convert the recognized gestures into audio output. The system employs advanced preprocessing and training techniques to ensure high accuracy. The effectiveness of the proposed CNN model is rigorously compared with traditional models, including K-Nearest Neighbors (KNN), Random Forest, Support Vector Machine (SVM), and Artificial Neural Network (ANN). Experimental results demonstrate the superior performance of the CNN-based approach, offering a robust and innovative solution for real-time gesture recognition and audio feedback.
Article Details
Unique Paper ID: 166794 Publication Volume & Issue: Volume 11, Issue 2 Page(s): 1795 - 1801
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