Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles

被引：0

作者：

Regmi, Hem ^{[1
]}

Tavasoli, Reza ^{[1
]}

Telaak, Joseph ^{[1
]}

Sur, Sanjib ^{[1
]}

Nelakuditi, Srihari ^{[1
]}

机构：

[1] Univ South Carolina, Dept Comp Sci & Engn, Columbia, SC 29208 USA

来源：

PROCEEDINGS OF THE 2024 THE 22ND ANNUAL INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS AND SERVICES, MOBISYS 2024 | 2024年

关键词：

Object Detection; Deep Learning; Millimeter-wave Radars;

D O I：

10.1145/3643832.3661416

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We propose AutoSense, a millimeter-wave(mmWave) wireless signal-based system for predicting 3D bounding boxes of vehicles. While cameras and LiDAR can be adversely affected by challenging-weather conditions such as heavy rain, fog, or snow, mmWave signals are less susceptible to these environmental factors, making them more resilient. As a result, AutoSense can complement other sensors for accurate 3D bounding box predictions in all weather conditions.

引用

页码：674 / 675

页数：2

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