TY - JOUR
T1 - A Dynamic Calibration Framework for the Event-Frame Stereo Camera System
AU - Hu, Rui
AU - Kogler, Jürgen
AU - Gelautz, Margrit
AU - Lin, Min
AU - Xia, Yuanqing
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Calibration and identification
KW - event cameras
KW - event-frame stereo camera system
KW - sensor fusion
UR - http://www.scopus.com/inward/record.url?scp=85208675615&partnerID=8YFLogxK
U2 - 10.1109/LRA.2024.3491426
DO - 10.1109/LRA.2024.3491426
M3 - Article
AN - SCOPUS:85208675615
SN - 2377-3766
VL - 9
SP - 11465
EP - 11472
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 12
ER -