@inproceedings{c04140b1d2f54772b728d97a8391943e,
title = "A hybrid computer vision and Wi-Fi Doppler radar system for capturing the 3-D hand gesture trajectory with a smartphone",
abstract = "This paper presents a 3-D hand gesture capture technique using the 2D camera and Wi-Fi connection signals of a smartphone. The motion detection principle of this technique involves combining the algorithm of pixel-based computer vision and the extraction of Doppler shift from the reflected Wi-Fi signals. Moreover, a joint displacement calibration procedure is proposed to transform the camera pixel coordinates to the radar space coordinates. This technique has the advantages of lower computation resources and power consumption than the current counterparts and requires no extra cameras and RF transmission sources when used on a smartphone.",
keywords = "3-D hand gesture detection, Hybrid motion detection system, Pixel-based computer vision, Wi-Fi Doppler radar",
author = "Tang, {Mu Cyun} and Chen, {Chien Lun} and Lin, {Min Hui} and Wang, {Fu Kang} and Yeh, {Chia Hung} and Horng, {Tzyy Sheng}",
note = "Funding Information: This work was supported in part by the Ministry of Science and Technology, Taiwan, under Grant 105-2221-E-110-016-MY3 and Grant 103-2221-E-110-013-MY3. Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE MTT-S International Microwave Symposium, IMS 2017 ; Conference date: 04-06-2017 Through 09-06-2017",
year = "2017",
month = oct,
day = "4",
doi = "10.1109/MWSYM.2017.8058834",
language = "English",
series = "IEEE MTT-S International Microwave Symposium Digest",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1251--1254",
booktitle = "2017 IEEE MTT-S International Microwave Symposium, IMS 2017",
}