On-device Real-time Hand Gesture Recognition

Chuo-Ling Chang
Esha Uboweja
Kanstantsin Sokal
Valentin Bazarevsky
ICCV Workshop on Computer Vision for Augmented and Virtual Reality, Montreal, Canada, 2021 (2021)
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Abstract

We present an on-device real-time hand gesture recogni-tion (HGR) system, which detects a set of predefined staticgestures from a single RGB camera. The system consists oftwo parts: a hand skeleton tracker and a gesture classifier.We improve and extend MediaPipe Hands [12] for the handtracker. We experiment with two different gesture classifiers,one heuristics based and one neural network (NN) based.