@inproceedings{464cbfa779f544459973948b7a315445,
title = "Time Domain Analysis for Extracting Spatial Distribution of Visible Light IDs",
abstract = "Extraction of spatial distribution of visible light IDs is useful to recognize spatially multiplexed ID signals which can be used to support automated rescue after a disaster. In this study, we investigate a time domain analysis to extract spatial distribution of visible light IDs. This method is based on an auto-correlation of temporal signals detected by using an image sensor and expected to be useful for real-time operation although both ID signal length and ID signal rate are required to be predefined. Our findings will be an important step in implementing a rescue support system with visible light IDs.",
keywords = "disaster, drone, imgae sensor, rescue, robot, visible light",
author = "Nobuhide Yokota and Hiroshi Yasaka and Kazuya Sugiyasu and Hideyuki Takahashi",
note = "Funding Information: ACKNOWLEDGMENT This work was supported by JSPS KAKENHI Grant Number 18KT0011. Publisher Copyright: {\textcopyright} 2022 IEEE.; 11th IEEE Global Conference on Consumer Electronics, GCCE 2022 ; Conference date: 18-10-2022 Through 21-10-2022",
year = "2022",
doi = "10.1109/GCCE56475.2022.10014136",
language = "English",
series = "GCCE 2022 - 2022 IEEE 11th Global Conference on Consumer Electronics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "426--427",
booktitle = "GCCE 2022 - 2022 IEEE 11th Global Conference on Consumer Electronics",
}