LECalib: Line-Based Event Camera Calibration

• URL: http://arxiv.org/abs/2512.22441v1
• Date: Sat, 27 Dec 2025 02:30:51 GMT
• Title: LECalib: Line-Based Event Camera Calibration
• Authors: Zibin Liu, Banglei Guana, Yang Shanga, Zhenbao Yu, Yifei Bian, Qifeng Yu,
• Abstract summary: Current event camera calibration methods involve using flashing patterns, reconstructing intensity images, and utilizing the features extracted from events.<n>We propose a line-based event camera calibration framework exploiting the geometric lines of commonly-encountered objects in man-made environments.<n>Our method detects lines directly from event streams and leverages an event-line calibration model to generate the initial guess of camera parameters.
• Score: 7.403100428984485
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Camera calibration is an essential prerequisite for event-based vision applications. Current event camera calibration methods typically involve using flashing patterns, reconstructing intensity images, and utilizing the features extracted from events. Existing methods are generally time-consuming and require manually placed calibration objects, which cannot meet the needs of rapidly changing scenarios. In this paper, we propose a line-based event camera calibration framework exploiting the geometric lines of commonly-encountered objects in man-made environments, e.g., doors, windows, boxes, etc. Different from previous methods, our method detects lines directly from event streams and leverages an event-line calibration model to generate the initial guess of camera parameters, which is suitable for both planar and non-planar lines. Then, a non-linear optimization is adopted to refine camera parameters. Both simulation and real-world experiments have demonstrated the feasibility and accuracy of our method, with validation performed on monocular and stereo event cameras. The source code is released at https://github.com/Zibin6/line_based_event_camera_calib.

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