Calibration is a classical issue in computer vision needed to retrieve 3D information from image measurements. This work presents a calibration approach for hybrid stereo rig involving multiple central camera types (perspective, flsheye, catadioptric). The paper extends the method of monocular perspective camera calibration using virtual visual servoing. The simultaneous intrinsic and extrinsic calibration of central cameras rig, using different models for each camera, is developed. The presented approach is suitable for the calibration of rigs composed by N cameras modelled by N different models. Calibration results, compared with state of the art approaches, and a 3D plane estimation application, allowed by the calibration, show the effectiveness of the approach. A cross-platform software implementing this method is available.

Altitude is one of the most important parameters to be known for an Unmanned Aerial Vehicle (UAV) especially during critical maneuvers such as landing or steady flight. In this paper, we present mixed stereoscopic vision system made of a fish-eye camera and a perspective camera for altitude estimation. Contrary to classical stereoscopic systems based on feature matching, we propose a plane sweeping approach in order to estimate the altitude and consequently to detect the ground plane. Since there exists a homography between the two views and the sensor being calibrated and the attitude estimated by the fish-eye camera, the algorithm consists then in searching the altitude which verifies this homography. We show that this approach is robust and accurate, and a CPU implementation allows a real time estimation. Experimental results on real sequences of a small UAV demonstrate the effectiveness of the approach.