EF-Calib: Spatiotemporal Calibration of Event- and Frame-Based Cameras Using Continuous-Time Trajectories
Shaoan Wang, Zhanhua Xin, Yaoqing Hu, Dongyue Li, Mingzhu Zhu, Junzhi, Yu

TL;DR
EF-Calib introduces a novel spatiotemporal calibration framework for event- and frame-based cameras using continuous-time trajectories, achieving high accuracy in intrinsic, extrinsic, and timing calibration for fused camera systems.
Contribution
The paper presents a new calibration pattern, an event recognition algorithm, and a derivable B-spline representation for continuous-time camera pose, enabling comprehensive calibration of event- and frame-based stereo systems.
Findings
Achieves state-of-the-art intrinsic parameter calibration accuracy.
Provides extrinsic calibration comparable to frame-based methods.
Accurately estimates time offset between cameras.
Abstract
Event camera, a bio-inspired asynchronous triggered camera, offers promising prospects for fusion with frame-based cameras owing to its low latency and high dynamic range. However, calibrating stereo vision systems that incorporate both event and frame-based cameras remains a significant challenge. In this letter, we present EF-Calib, a spatiotemporal calibration framework for event- and frame-based cameras using continuous-time trajectories. A novel calibration pattern applicable to both camera types and the corresponding event recognition algorithm is proposed. Leveraging the asynchronous nature of events, a derivable piece-wise B-spline to represent camera pose continuously is introduced, enabling calibration for intrinsic parameters, extrinsic parameters, and time offset, with analytical Jacobians provided. Various experiments are carried out to evaluate the calibration performance…
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Taxonomy
TopicsMedical Imaging Techniques and Applications · CCD and CMOS Imaging Sensors · Advanced Optical Sensing Technologies
