Targetless Camera Calibration

In photogrammetry a camera is considered calibrated if its interior orientation parameters are known. These encompass the principal distance, the principal point position and some Additional Parameters used to model possible systematic errors. The current state of the art for automated camera calibration relies on the use of coded targets to accurately determine the image correspondences. This paper presents a new methodology for the efficient and rigorous photogrammetric calibration of digital cameras which does not require any longer the use of targets. A set of images depicting a scene with a good texture are sufficient for the extraction of natural corresponding image points. These are automatically matched with feature-based approaches and robust estimation techniques. The successive photogrammetric bundle adjustment retrieves the unknown camera parameters and their theoretical accuracies. Examples, considerations and comparisons with real data and different case studies are illustrated to show the potentialities of the proposed methodology.