@inproceedings{a81027c1befb4da5bcab9b455c22ada8,
title = "An MAE-Aware ROI Sampling Model for LiDAR",
abstract = "Light Detection and Ranging (LiDAR) sensors have relatively low resolutions, require considerable time to acquire the laser range measurement, and store large-scale point clouds. In order to address these issues, this paper presents a sampling algorithm which finds the optimal sampling rates in a region of interest (ROI) to minimize the total mean-Absolute-error (MAE). Eventually, MAEs in both ROIs and overall scene decrease significantly. Experimental results show that the proposed scheme reduces the MAE in the object area by up to 63.3\% and that in the overall scene by up to 34.2\%.",
keywords = "LiDAR, MAE, ROI, sampling, segmentation",
author = "Pham, \{Quan Dung\} and Nguyen, \{Xuan Truong\} and Lee, \{Hyuk Jae\} and Hyun Kim",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 17th International System-on-Chip Design Conference, ISOCC 2020 ; Conference date: 21-10-2020 Through 24-10-2020",
year = "2020",
month = oct,
day = "21",
doi = "10.1109/ISOCC50952.2020.9333034",
language = "English",
series = "Proceedings - International SoC Design Conference, ISOCC 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "276--277",
booktitle = "Proceedings - International SoC Design Conference, ISOCC 2020",
}