@inproceedings{27f783a453f8458098f3851600f97aa1,
title = "Distortion-Free BEV Generation Method with Complete Ground Information",
abstract = "As an important part of vehicle assisted driving, Bird Eye View (BEV) can not only effectively improve driving safety, but also participate in the control decision-making of unmanned driving as a data source of ground information. Therefore, it is necessary to generate a distortionless BEV with complete ground information. In this paper, through in-depth study of the imaging and de-distortion characteristics of fisheye cameras, iterative calibration and FOV overlapping area weighted fusion methods are introduced into the existing methods to solve the existing BEV generation problems, such as loss of ground information and imperfect matching of Field of View (FOV) overlapping areas, due to the special distortion characteristics of vehicle-mounted fisheye cameras and actual installation restrictions. The experimental results show that the improved BEV generation method has higher computational efficiency and image quality.",
keywords = "BEV, Fish Eye Camera, Iterative Calibration, Weighted Fusion",
author = "Lin Yang and Shihang Wu and Zhiwei Li and Haiou Liu",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.; 2nd CCF Intelligent Vehicles Symposium, CIVS 2024 ; Conference date: 19-10-2024 Through 20-10-2024",
year = "2025",
doi = "10.1007/978-981-95-0848-8\_2",
language = "English",
isbn = "9789819508471",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "13--24",
editor = "Huiyun Li and Peng Sun and Daxin Tian and Zhengguo Sheng and Victor Leung and Huaxia Xia and Yong Hong",
booktitle = "Intelligent Vehicles - 2nd CCF Intelligent Vehicles Symposium, CIVS 2024, Revised Selected Papers",
address = "Germany",
}