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惠念(博士生)、蔡忠亮等的論文在REMOTE SENSING 刊出
發布時間:2025-02-02     發布者:易真         審核者:任福     浏覽次數:

标題: EOR: An Enhanced Object Registration Method for Visual Images and High-Definition Maps

作者: Hui, NA (Hui, Nian); Jiang, ZJ (Jiang, Zijie); Cai, ZL (Cai, Zhongliang); Ying, S (Ying, Shen)

來源出版物: REMOTE SENSING : 17 : 1 文獻号: 66 DOI: 10.3390/rs17010066 Published Date: 2025 JAN

摘要: Accurate object registration is crucial for precise localization and environment sensing in autonomous driving systems. While real-time sensors such as cameras and radar capture the local environment, high-definition (HD) maps provide a global reference frame that enhances localization accuracy and robustness, especially in complex scenarios. In this paper, we propose an innovative method called enhanced object registration (EOR) to improve the accuracy and robustness of object registration between camera images and HD maps. Our research investigates the influence of spatial distribution factors and spatial structural characteristics of objects in visual perception and HD maps on registration accuracy and robustness. We specifically focus on understanding the varying importance of different object types and the constrained dimensions of pose estimation. These factors are integrated into a nonlinear optimization model and extended Kalman filter framework. Through comprehensive experimentation on the open-source Argoverse 2 dataset, the proposed EOR demonstrates the ability to maintain high registration accuracy in lateral and elevation dimensions, improve longitudinal accuracy, and increase the probability of successful registration. These findings contribute to a deeper understanding of the relationship between sensing data and scenario understanding in object registration for vehicle localization.

作者關鍵詞: high-definition map; registration; visual localization; autonomous driving; cross modality

地址: [Hui, Nian; Jiang, Zijie; Cai, Zhongliang; Ying, Shen] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

通訊作者地址: Cai, ZL (通訊作者)Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

電子郵件地址: huinian@whu.edu.cn; jiangzijie@whu.edu.cn; zlcai@whu.edu.cn; shy@whu.edu.cn

影響因子:4.2
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