Camera calibration with lens distortion from low-rank textures

Abstract

A 'Camera Calibrator' provides various techniques for recovering intrinsic camera parameters and distortion characteristics by processing a set of one or more input images. These techniques are based on extracting 'Transform Invariant Low-Rank Textures' (TILT) from input images using high-dimensional convex optimization tools for matrix rank minimization and sparse signal recovery. The Camera Calibrator provides a simple, accurate, and flexible method to calibrate intrinsic parameters of a camera even with significant lens distortion, noise, errors, partial occlusions, illumination and viewpoint change, etc. Distortions caused by the camera can then be automatically corrected or removed from images. Calibration is achieved under a wide range of practical scenarios, including using multiple images of a known pattern, multiple images of an unknown pattern, single or multiple images of multiple patterns, etc. Significantly, calibration is achieved without extracting or manually identifying low-level features such as corners or edges from the calibration images.