@inproceedings{8708d432fbfe44cbb39b6bf1fef0c018,
title = "Depth Static Hand Gesture Recognition",
abstract = "Finger-spelling recognition is the popular way to realize Human-Computer Interaction (HCI). The sign language datasets for finger-spelling recognition are mostly collected by the color camera and the depth camera. The depth camera directly captures the 3D information between the performer and lens, which can extract the precise hand gesture texture information without being influenced by the complex background and illumination. This work develops a hand gesture recognition system using depth image. This system employs a VGGNet to learn the feature extraction and classification. The experimental results show that the proposed hand gesture recognition system can correctly recognize the hand gesture using only depth image. This may reduce computational cost of the hand gesture recognition system.",
author = "Cheng, {Yao Mao} and Huang, {Jyun Wei} and Sung, {Chi Yu} and Li, {Bo Wei} and Chen, {Yu Chieh} and Yang, {Shih Hung} and Chen, {Yon Ping}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 International Automatic Control Conference, CACS 2021 ; Conference date: 03-11-2021 Through 06-11-2021",
year = "2021",
doi = "10.1109/CACS52606.2021.9638710",
language = "English",
series = "2021 International Automatic Control Conference, CACS 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 International Automatic Control Conference, CACS 2021",
address = "美國",
}