A do-it-yourself computer vision based robotic ball throw trainer

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Abstract

We demonstrate a self-training system for sports involving throwing a ball. We design a do-it-yourself (DIY) machinery that can be assembled using off-the-shelf items and integrates computer vision to visually track the ball throw accuracy. In this work, we demonstrate a system that can identify if the ball went through the hoop and approximately in which of the hoop's inner region. We envision that this preliminary design sets the foundation for a complete DIY sports IoT system that involves a hoola hoop, RaspberryPi, PiCamera and a LED strip, along with advanced ball placement and dynamics tracking.

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APA

Tharpe, B., Bourgeois, A. G., & Ashok, A. (2021). A do-it-yourself computer vision based robotic ball throw trainer. In MobiSys 2021 - Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services (pp. 505–506). Association for Computing Machinery, Inc. https://doi.org/10.1145/3458864.3466909

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