eKalibr-Stereo: Continuous-Time Spatiotemporal Calibration for Event-Based Stereo Visual Systems

Abstract

The bioinspired event camera, distinguished by its exceptional temporal resolution, high dynamic range, and low power consumption, has been extensively studied in recent years for motion estimation, robotic perception, and object detection. In ego-motion estimation, the stereo event camera setup is commonly adopted due to its direct scale perception and depth recovery. For optimal stereo visual fusion, accurate spatiotemporal (extrinsic and temporal) calibration is required. In this letter, we present <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eKalibr-Stereo</i>, an accurate spatiotemporal calibrator for event-based stereo visual systems, utilizing the widely used circular grid board. To ensure the continuity of grid pattern tracking, building upon the grid pattern recognition method in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eKalibr</i>, an additional motion prior-based tracking module is designed in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eKalibr-Stereo</i> to track incomplete grid patterns. Based on tracked grid patterns, a two-step initialization procedure is performed to recover initial guesses of piece-wise B-splines and spatiotemporal parameters, followed by a continuous-time batch bundle adjustment to refine the initialized states to optimal ones. The results of extensive real-world experiments show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eKalibr-Stereo</i> can achieve accurate event-based stereo spatiotemporal calibration. The implementation of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eKalibr-Stereo</i> is open-sourced at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/Unsigned-Long/eKalibr</uri> to benefit the research community.