On-device Real-time Hand Gesture Recognition

• URL: http://arxiv.org/abs/2111.00038v1
• Date: Fri, 29 Oct 2021 18:33:25 GMT
• Title: On-device Real-time Hand Gesture Recognition
• Authors: George Sung, Kanstantsin Sokal, Esha Uboweja, Valentin Bazarevsky, Jonathan Baccash, Eduard Gabriel Bazavan, Chuo-Ling Chang, Matthias Grundmann
• Abstract summary: We present an on-device real-time hand gesture recognition (HGR) system, which detects a set of predefined static gestures from a single RGB camera. We use MediaPipe Hands as the basis of the hand skeleton tracker, improve the keypoint accuracy, and add the estimation of 3D keypoints in a world metric space.
• Score: 1.4658400971135652
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present an on-device real-time hand gesture recognition (HGR) system, which detects a set of predefined static gestures from a single RGB camera. The system consists of two parts: a hand skeleton tracker and a gesture classifier. We use MediaPipe Hands as the basis of the hand skeleton tracker, improve the keypoint accuracy, and add the estimation of 3D keypoints in a world metric space. We create two different gesture classifiers, one based on heuristics and the other using neural networks (NN).

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