AUTOMATIC TEXTURE MAPPING WITH AN OMNIDIRECTIONAL CAMERA MOUNTED ON A VEHICLE TOWARDS LARGE SCALE 3D CITY MODELS
Keywords: Extended Kalman filter, Structure from Motion, Texture mapping, Panoramic images
Abstract. Today high resolution panoramic images with competitive quality have been widely used for rendering in some commercial systems. However the potential applications such as mapping, augmented reality and modelling which need accurate orientation information are still poorly studied. Urban models can be quickly obtained from aerial images or LIDAR, however with limited quality or efficiency due to low resolution textures and manual texture mapping work flow. We combine an Extended Kalman Filter (EKF) with the traditional Structure from Motion (SFM) method without any prior information based on a general camera model which can handle various kinds of omnidirectional and other kind of single perspective image sequences even with unconnected or weakly connected frames. The orientation results is then applied to mapping the textures from panoramas to the existing building models obtained from aerial photogrammetry. It turns out to largely improve the quality of the models and the efficiency of the modelling procedure.