Abstract—On the one hand, cameras of conventional field-of- view usually considered in computer vision and robotics are very often modeled as a pinhole plus possibly a distortion model. On the other hand, there is a large variety of models for panoramic cameras. Many camera models have been proposed for fisheye cameras, catadioptric cameras, and super fisheye cameras. But in both cases, few models offer the possibility of converting them into another model.This paper contributes to filling this gap in, to allow an algo- rithm designed with a projection model to accept data of a cam- era calibrated with another model. So, a pre-existing data set can be used without having to recalibrate the camera. We pro- vide the methodology and mathematical developments for three conversions considering three different types of cameras that are evaluated with respect to calibration and within a visual Si- multaneous Localization And Mapping benchmark. The source code of the camera model conversions studied in this paper is shared within the libPeR library for Perception in Robotics: https://github.com/PerceptionRobotique/libPeR_base.