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MediaPipe Hands: On-device Real-time Hand Tracking

小编 映维   |   分类：CV / XR   |  

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PubDate: June 2020

Teams: Google Research

Writers: Fan Zhang, Valentin Bazarevsky, Andrey Vakunov, George Sung, Chuo-Ling Chang, Matthias Grundmann, Andrei Tkachenka

PDF: MediaPipe Hands: On-device Real-time Hand Tracking

Project: MediaPipe Hands: On-device Real-time Hand Tracking

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 source at https://mediapipe.dev.

本文链接：https://paper.nweon.com/2702

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