BlazePose GHUM Holistic: Real-time 3D Human Landmarks and Pose Estimation
Ivan Grishchenko, Valentin Bazarevsky, Andrei Zanfir, Eduard Gabriel Băzăvan, Mihai Zanfir, Richard W. Yee, Karthik Raveendran, Matsvei Zhdanovich, Matthias Grundmann, Cristian Sminchisescu · arXiv (Cornell University) · 2022
We present BlazePose GHUM Holistic, a lightweight neural network pipeline for 3D human body landmarks and pose estimation, specifically tailored to real-time on-device inference. BlazePose GHUM Holistic enables motion capture from a single RGB image including avatar control, fitness tracking and AR/VR effects. Our main contributions include i) a novel method for 3D ground truth data acquisition, ii) updated 3D body tracking with additional hand landmarks and iii) full body pose estimation from a monocular image.