A Dynamic Calibration Framework for the Event-Frame Stereo Camera System

IF 4.6 2区 计算机科学 Q2 ROBOTICS IEEE Robotics and Automation Letters Pub Date : 2024-11-04 DOI:10.1109/LRA.2024.3491426
Rui Hu;Jürgen Kogler;Margrit Gelautz;Min Lin;Yuanqing Xia
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Abstract

The fusion of event cameras and conventional frame cameras is a novel research field, and a stereo structure consisting of an event camera and a frame camera can incorporate the advantages of both. This letter develops a dynamic calibration framework for the event-frame stereo camera system. In this framework, the first step is to complete the initial detection on a circle-grid calibration pattern, and a sliding-window time matching method is proposed to match the event-frame pairs. Then, a refining method is devised for two cameras to get the accurate information of the pattern. Particularly, for the event camera, a patch-size motion compensation method with high computational efficiency is designed to achieve time synchronization for two cameras and fit circles in an image of warped events. Finally, the pose between two cameras is globally optimized by constructing a pose-landmark graph with two types of edges. The proposed calibration framework has the advantages of high real-time performance and easy deployment, and its effectiveness is verified by experiments based on self-recorded datasets.
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事件帧立体相机系统的动态校准框架
事件相机与传统框架相机的融合是一个新的研究领域,而由事件相机和框架相机组成的立体结构可以兼具两者的优点。本文为事件帧立体相机系统开发了一个动态校准框架。在该框架中,第一步是在圆网格校准模式上完成初始检测,并提出一种滑动窗口时间匹配方法来匹配事件帧对。然后,针对两台摄像机设计了一种细化方法,以获得图案的准确信息。特别是针对事件摄像机,设计了一种具有高计算效率的补丁大小运动补偿方法,以实现两台摄像机的时间同步,并在翘曲事件图像中拟合圆形。最后,通过构建具有两类边的姿态地标图,对两台摄像机之间的姿态进行全局优化。所提出的校准框架具有实时性高、易于部署等优点,其有效性已通过基于自记录数据集的实验得到验证。
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来源期刊
IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters Computer Science-Computer Science Applications
CiteScore
9.60
自引率
15.40%
发文量
1428
期刊介绍: The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.
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