Poster: MilliCloud: Beyond Vision PCD Generation using Millimeter-Wave

被引:0
|
作者
Cai, Pingping [1 ]
Sur, Sanjib [1 ]
机构
[1] Univ South Carolina, Comp Sci & Engn, Columbia, SC 29208 USA
来源
PROCEEDINGS OF THE 2022 THE 23RD ANNUAL INTERNATIONAL WORKSHOP ON MOBILE COMPUTING SYSTEMS AND APPLICATIONS (HOTMOBILE '22) | 2022年
关键词
Millimeter-Wave; Graph Neural Networks; Point Cloud Data;
D O I
10.1145/3508396.3517071
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Existing 3D Point Cloud Data (PCD) generation systems based on RGB-D and LiDAR sensors require robust lighting and unobstructed field of views of target scenes. So, they cannot work properly under challenging environmental conditions. Recently, millimeter-wave (mmWave) based imaging systems have raised a huge interest due to their ability to see-through obstacles and work in dark environments. But the resolution and quality of the PCDs from traditional imaging algorithms are very poor. This work proposes and preliminary validates MilliCloud, a deep-learning based system for generating high-quality indoor PCDs using handheld mmWave devices.
引用
收藏
页码:123 / 124
页数:2
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