P squared Calib: Utilizing Pattern Priors for LiDAR-Camera Extrinsic Calibration

Target-based LiDAR-camera extrinsic calibration is a prerequisite for multi-sensor fusion in robotics. However, in the widely adopted four-hole pipeline,. This paper presents P squared Calib, which exploits pattern priors, geometric constraints specified by the CAD model of the target board, to improve calibration accuracy. First, we incorporate the known hole radius as a fitting constraint to prevent center estimates from degrading under sparse angular coverage. Building on the improved hole estimates, we further enforce the rigid rectangular layout of the four holes as a global consistency constraint to correct residual errors across holes. Both priors are integrated into an. Experiments on simulated and real datasets show that P squared Calib reduces the joint registration residual by 90% and 82% and the held-out reprojection error by 96% and 77% over the baseline. We will release the code and data to facilitate future research.