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Paper FrAT17.7

Dong, Pengfei (Xi’an Jiaotong University), Hai, Renwei (Xi'an Jiaotong University), Shen, Yanqing (Xi'an Jiaotong University), Zhu, Ziyu (Xi'an Jiaotong University), Chen, Shitao (Xi'an Jiaotong University, Xi'an, China), Xin, Jingmin (Xi'an Jiaotong University), Zheng, Nanning (Xi'an Jiaotong University)

EventAlign: LiDAR-Event Camera Calibration with Event Alignment Loss

Scheduled for presentation during the Poster Session "Transportation Data Analysis and Calibration" (FrAT17), Friday, September 27, 2024, 10:30−12:30, Foyer

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 3, 2024

Keywords Sensing, Vision, and Perception, Driver Assistance Systems

Abstract

近年来,事件摄像机作为一种仿生灵感 传感器,在以下领域变得越来越重要 机器人和自动驾驶。鉴于事件本质上缺乏深度信息,因此 采用多传感器方案,将事件和 LiDAR 扫描,其性能在很大程度上取决于精度 不同传感器之间的校准。然而,由于事件的独特表现形式 相机,只捕捉没有纹理的动态物体 结构,大多数以前的事件校准方法 摄像机具有复杂的设置和受控照明 条件。在本文中,我们提出了一种新型的外在校准方法 通过使用 LiDAR 模拟事件的方法,该方法不会 需要传感器本身以外的任何设备。具体来说,我们首先从 LiDAR 事件中提取 连续的原始点云。然后应用聚类算法来优化此事件 数据并识别运动质心。最后,提出了一种两步优化过程: &#

 

 

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