Rolling Shutter Camera Self-Calibration

Abstract

Rolling shutter (RS) cameras are widely used in consumerdevices, but their row-wise exposure causes distortions under motion,making geometric 3D vision problems dependent on both camera in-trinsics and readout time ratio. Existing RS calibration methods relyon calibration targets or specialised hardware, limiting their use in un-constrained settings. We present the first self -calibration method forRS cameras that directly estimates camera intrinsics and the readouttime ratio from image sequences, without requiring calibration targets.The method is implemented as a self-calibrating bundle adjustment(BA), which critically depends on the RS imaging model. We com-bine two known complementary models. The first formulates RS imag-ing as continuous-time trajectory estimation under a row-wise pose rep-resentation. The second interprets RS images as temporally distortedglobal shutter (GS) images and requires to estimate correction fields.The combination is non-trivial and results in a unified dual-projectionmodel, in which each 3D point is simultaneously constrained at both row-dependent and reference timestamps along a shared continuous trajec-tory, enforcing stronger geometric and temporal consistency. Extensivesimulations analyse the applicability of several implementations undervarying conditions, and real data experiments demonstrate the accuracy,robustness, and practical effectiveness of the proposed approach.