USVTrack: 内陸水路の自動運転のためのUSVベース4Dレーダーカメラ追跡データセット
USVTrack: USV-Based 4D Radar-Camera Tracking Dataset for Autonomous Driving in Inland Waterways
内陸水路での自律航行に向けて、4Dレーダーと単眼カメラを搭載した無人水上艇で収集した初の追跡データセットUSVTrackを構築し、レーダーカメラマッチング手法RCMの有効性を示した。
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著者: Shanliang Yao, Runwei Guan, Yi Ni, Sen Xu, Yong Yue, Xiaohui Zhu, Ryan Wen Liu
分類: cs.CV, cs.RO
原文アブストラクト
Object tracking in inland waterways plays a crucial role in safe and cost-effective applications, including waterborne transportation, sightseeing tours, environmental monitoring and surface rescue. Our Unmanned Surface Vehicle (USV), equipped with a 4D radar, a monocular camera, a GPS, and an IMU, delivers robust tracking capabilities in complex waterborne environments. By leveraging these sensors, our USV collected comprehensive object tracking data, which we present as USVTrack, the first 4D radar-camera tracking dataset tailored for autonomous driving in new generation waterborne transportation systems. Our USVTrack dataset presents rich scenarios, featuring diverse various waterways, varying times of day, and multiple weather and lighting conditions. Moreover, we present a simple but effective radar-camera matching method, termed RCM, which can be plugged into popular two-stage association trackers. Experimental results utilizing RCM demonstrate the effectiveness of the radar-camera matching in improving object tracking accuracy and reliability for autonomous driving in waterborne environments. The USVTrack dataset is public on https://usvtrack.github.io.
