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VeriCalib: A Verifiable Target-Based LiDAR-Camera Calibration Method
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Xiangcheng Hu et al. propose VeriCalib, which models target-based LiDAR-camera extrinsic calibration as a verifiable estimation problem and outputs a calibration status to indicate whether to accept the result or collect additional data. The method uses structured covariance to jointly propagate the uncertainty of camera and LiDAR target features (combined with known geometric priors), and estimates its scale from the residuals; it also designs intra-view and cross-view checks, with thresholds that maintain the significance level even when the noise level is unknown. It decouples rotation and translation to localize the precision in each direction and guide data collection to supplement the weakest direction.
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- VeriCalib: Verifiable Target-Based LiDAR-Camera Calibration
VeriCalib formulates target-based LiDAR-camera extrinsic calibration as a verifiable estimation problem and outputs a calibration state indicating whether to accept the result or collect more data. It uses a structured covariance to decouple rotation and translation accuracy, guiding data collection toward the weakest directions, and uses in-view and cross-view checks plus the minimum detectable deviation to define the smallest fault detectable in each direction.
arXiv cs.RO ·