@inproceedings{d9e1e73e5c304308b4a19797ab148035,
title = "Live Demonstration: Home Appliance Control System with Dynamic Hand Gesture Recognition base on 3D Hand Skeletons",
abstract = "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.",
keywords = "convolutional neural networks, dynamic hand gesture recognition, home appliance application, skeleton",
author = "Tsai, {Tsung Han} and Luo, {Yi Jhen} and Wan, {Wei Chung}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022 ; Conference date: 13-06-2022 Through 15-06-2022",
year = "2022",
doi = "10.1109/AICAS54282.2022.9870006",
language = "???core.languages.en_GB???",
series = "Proceeding - IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "503",
booktitle = "Proceeding - IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022",
}