@inproceedings{ad558c2b4d8e44e9a48219c0808e2e07,
title = "3D Human Target Tracking and Localization Based on Millimeter Wave Radar and Visual Fusion",
abstract = "In recent years, 3D object detection has become an important component in the fields of autonomous driving and mobile robots. Current vision-based methods may fail to achieving reliable positioning of a 3D object due to the sensing limitations of a camera sensor. In this paper, we consider a more practical object perception pipeline using combined information from both a monocular camera and a 4D millimeter-wave radar (MMWR). Initially, the human body is detected in the 2D image plane of camera to aid the human body segmentation in 4D radar point clouds. Then the detection results from both the camera and the MMWR, including the doppler velocity of the point cloud, are used as measurement to feed an Kalman filter estimator backend to realize the rapid localization of human targets.",
keywords = "3D object tracking, Kalman filter, Millimeter wave Radar, Monocular camera, YOLOv8",
author = "Haochen Chai and Zhenghao Zou and Chunhui Zhao and Quan Pan and Yang Lyu",
note = "Publisher Copyright: {\textcopyright} Beijing HIWING Scientific and Technological Information Institute 2024.; 3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023 ; Conference date: 09-09-2023 Through 11-09-2023",
year = "2024",
doi = "10.1007/978-981-97-1103-1_35",
language = "英语",
isbn = "9789819711024",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "392--402",
editor = "Yi Qu and Mancang Gu and Yifeng Niu and Wenxing Fu",
booktitle = "Proceedings of 3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023 - Volume 7",
}