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Playing Rock-Paper-Scissors Using AI Through OpenCV
Abstract
Day-to-day life has become smarter and more intertwined with technology in the modern era. We can chat with AI chatbots, and we can play with AI machines. In many cases, AI machines are defeating human players. All age groups are likely to play these games. The computer gaming industry has found Artificial intelligence as a necessary element to make more entertaining and challenging games. This work involves the integration of rock-paper-scissors (RPS) game with artificial intelligence (AI) using OpenCV and MediaPipe. Through collaboration with designers and animators, the framework is designed to be computationally light while also entertaining and visually appealing. To evaluate kinematic hand data in Python, the basic gesture recognition pipeline emp1oys a 1eap motion device and two distinct machine 1earning architectures. This proposed system will provide a powerful application for future research into social human-machine interaction.
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