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arXiv · 2006.10214

MediaPipe Hands: On-device Real-time Hand Tracking

Fan Zhang·Valentin Bazarevsky·Andrey Vakunov·Andrei Tkachenka·George Sung·Chuo-Ling Chang·Matthias Grundmann
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Abstract

We present a real-time on-device hand tracking pipeline that predicts hand skeleton from single RGB camera for AR/VR applications. The pipeline consists of two models: 1) a palm detector, 2) a hand landmark model. It's implemented via MediaPipe, a framework for building cross-platform ML solutions. The proposed model and pipeline architecture demonstrates real-time inference speed on mobile GPUs and high prediction quality. MediaPipe Hands is open sourced at https://mediapipe.dev.

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Fan Zhang, Valentin Bazarevsky, Andrey Vakunov, Andrei Tkachenka, George Sung, Chuo-Ling Chang, Matthias Grundmann. 2020-06-18. MediaPipe Hands: On-device Real-time Hand Tracking. https://arxiv.org/abs/2006.10214

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