A New Non-Central Model for Fisheye Calibration

Radka Tezaur, Avinash Kumar, Oscar Nestares; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2022, pp. 5222-5231


A new non-central model suitable for calibrating fisheye cameras is proposed. It is a direct extension of the popular central model developed by Scaramuzza et al., used by Matlab Computer Vision Toolbox fisheye calibration tool. It allows adapting existing applications that are using this central model to a non-central projection that is more accurate, especially when objects captured in the images are close to the camera, and it makes it possible to switch easily between the more accurate non-central characterization of the fisheye camera and the more convenient central approximation, as needed. It is shown that the algorithms proposed by Scaramuzza et al. for their central model can be modified to accommodate the angle dependent axial viewpoint shift. This means, besides other, that a similar process can be used for calibration involving the viewpoint shift characterization and a user-friendly calibration tool can be produced with this new non-central model that does not require the user to provide detailed lens design specifications or an educated guess for the initial parameter values. Several other improvements to the Scaramuzza's central model are also introduced, helping to improve the performance of both the central model, and its non-central extension.

Related Material

@InProceedings{Tezaur_2022_CVPR, author = {Tezaur, Radka and Kumar, Avinash and Nestares, Oscar}, title = {A New Non-Central Model for Fisheye Calibration}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2022}, pages = {5222-5231} }