Event cameras, inspired by biological vision, offer high dynamic range, excellent temporal resolution, and minimal data redundancy. Precise calibration of event camera systems is essential for applications such as 3D vision. The cessation of extra gray frame production in popular models like the dynamic vision sensor (DVS) poses significant challenges to achieving high-accuracy calibration. Traditional calibration methods, which rely on motion to trigger events, are prone to movement-related errors. This paper introduces a motion-error-free calibration method for event cameras using a flashing target produced by a standard electronic display that elicits high-fidelity events. We propose an improved events-accumulator to reconstruct gray images with distinct calibration features and develop an optimization method that adjusts camera parameters and control point positions simultaneously, enhancing the calibration accuracy of event camera systems. Experimental results demonstrated higher accuracy compared to the traditional motion-based calibration method (reprojection error: 0.03 vs. 0.96 pixels). The 3D reconstruction error remained around 0.15 mm, significantly improving over the motion-based method's 8.00 mm. Additionally, the method's adaptability for hybrid calibration in event-based stereovision systems was verified (e.g., with frame cameras or projectors).

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http://dx.doi.org/10.1364/OE.529263DOI Listing

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