Gaming using different hand gestures using artificial neural network

Abstract

INTRODUCTION: Gaming has evolved over the years, and one of the exciting developments in the industry is the integration of hand gesture recognition.
 OBJECTIVES: This paper proposes gaming using different hand gestures using Artificial Neural Networks which allows players to interact with games using natural hand movements, providing a more immersive and intuitive gaming experience.
 METHODS: Introduces two modules: recognition and analysis of gestures. The gesture recognition module identifies the gestures, and the analysis module assesses them to execute game controls based on the calculated analysis.
 RESULTS: The main results obtained in this paper are enhanced accessibility, higher accuracy and improved performance.
 CONCLUSION: To communicate with any of the traditional systems, physical contact is necessary. In the hand gesture recognition system, the same functionality can be interpreted by gestures without requiring physical contact with the interfaced devices.