Parsing the Hand Gesture of Traffic Police Officers by Using OpenPose

DOI

10.2991/aebmr.k.220502.009How to use a DOI?

Keywords

Hand gesture parsing; traffic hand gesture; 3-D movement Tracker; OpenPose

Abstract

Nowadays, as self-driving cars become more and more popular, more features should be added to the whole function of self-driving cars. One of them should be the ability to parse the hand gestures of traffic police officers. To fully bring self-driving cars to reality, such a feature should be discussed and considered in their functionality. In recent decades, real-time 3D hand pose estimation combined with depth cameras has contributed to the successful launch of virtual reality and augmented reality applications. This essay focuses on using OpenPose to parse the hand gestures of traffic police officers based on the expected functionality of self-driving cars. Based on the given background, this article will use comparison to separate the traditional methods and the new method. The result generated by OpenPose is faster and more accurate (99% accuracy), so that it can be a choice for the future algorithm of recognition of hand gesture recognition of traffic officers in self-driving cars.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license.

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TY  - CONF
AU  - Maogen Fu
PY  - 2022
DA  - 2022/05/16
TI  - Parsing the Hand Gesture of Traffic Police Officers by Using OpenPose
BT  - Proceedings of the 2022 International Conference on Urban Planning and Regional Economy（UPRE 2022）
PB  - Atlantis Press
SP  - 38
EP  - 42
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.220502.009
DO  - 10.2991/aebmr.k.220502.009
ID  - Fu2022
ER  -