Live Demonstration: Home Appliance Control System with Dynamic Hand Gesture Recognition base on 3D Hand Skeletons

被引：1
|
作者：
Tsai, Tsung-Han [1 ]
Luo, Yi-Jhen [1 ]
Wan, Wei-Chung [1 ]
机构：
[1] Natl Cent Univ, Dept Elect Engn, Taoyuan, Taiwan
来源：
2022 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE CIRCUITS AND SYSTEMS (AICAS 2022): INTELLIGENT TECHNOLOGY IN THE POST-PANDEMIC ERA | 2022年
关键词：
dynamic hand gesture recognition; convolutional neural networks; skeleton; home appliance application;
D O I：
10.1109/AICAS54282.2022.9870006
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we present a two-stage lightweight convolutional neural network architecture on hand gesture recognition for home appliance control system. At the first stage, we utilize DetNet to detect the hand and generate 3D hand skeleton locations. At the second stage, a skeleton-based dynamic hand gesture recognition model is developed. We have 99.4% accuracy by the trained CNN model with our testing dataset. Besides, we implement this system on the Nvidia Jetson AGX Xavier to control the on/off of the fan and the light and the overall system achieve 15 fps.
引用
收藏
页码：503 / 503
页数：1
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