Using Google MediaPipe to Develop an Innovative Motion-Sensing Game

Abstract

This paper combines AI, motion-sensing games, and healthcare to propose an innovative motion-sensing game framework based on AI technology. We aim to address the current issue of people's lack of exercise. In this paper, we use the multimedia machine learning tools developed by Google MediaPipe to transform the once-popular arcade game Breakout into a motion-sensing Breakout game.

In our experiments, we found that MediaPipe can misjudge in complex scenarios. However, to ensure a smooth experience with the motion-sensing Breakout game, we proposed an improved algorithm to resolve MediaPipe's misjudgments. To enhance user engagement, we also developed a two-player mode and incorporated calorie consumption estimation during the gameplay. This aims to motivate people to exercise more and improve their health. From our experiences, the motion-sensing Breakout game indeed sparks people's interest in exercise and helps them achieve physical activity through the gameplay.

Keywords: Google Mediapipe, Breakout game, Motion-Sensing Game, motion-sensing Breakout game.

Author
Hsien-Leing Tsai