preprintarXiv (Cornell University)Jun 18, 2020GREEN OA

MediaPipe Hands: On-device Real-time Hand Tracking

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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.

Citation impact

550
total citations
FWCI
Percentile
References
10
Citations per year

Authors

7

Topics & keywords

Keywords
  • Pipeline (software)
  • Computer science
  • Tracking (education)
  • Computer vision
  • RGB color model
  • Landmark
  • Inference
  • Real-time computing
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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