Innovation Owner
Mr. NONTAPAT WANNACHOTE
Student
Details
This research focuses on developing a hand gesture recognition system using machine learning and computer vision to control electronic devices like drones and robots with high speed and accuracy.
This research will begin with a review of literature and related studies to examine existing technologies and methods for hand gesture recognition and their applications in controlling electronic devices such as drones, robots, and gaming systems. Subsequently, a hand gesture recognition system will be designed and developed using machine learning and computer vision techniques, with a focus on creating an algorithm that operates quickly and accurately, making it suitable for real-time control.
The developed system will be tested and refined using various simulated scenarios to evaluate its efficiency and accuracy in diverse environments. Additionally, a user-friendly interface will be developed to ensure accessibility for all user groups. The research will also incorporate qualitative studies to gather feedback from both novice users and experts, which will contribute to further system improvements, ensuring it effectively meets user needs.
Ultimately, the findings of this research will lead to the development of a functional prototype for gesture-based control, which can be applied in industries and entertainment. This will contribute to advancements in innovation and new technologies in the future.
Objective
The objective is to develop a highly accurate, user-friendly hand gesture recognition system using Computer Vision and AI, allowing for customizable gesture controls.
The research on the development of hand gesture recognition for controlling electronic devices aims to create a high-precision system capable of operating in diverse environments while remaining user-friendly for all groups. It focuses on applying Computer Vision and Artificial Intelligence (AI) to enhance gesture recognition efficiency. Furthermore, the research aims to study the design of effective and intuitive gesture sets for various electronic devices, ensuring ease of learning and memorization, as well as developing a system that allows users to customize gesture controls according to their individual preferences.