Texturizing and Refinement of 3D City Models with Mobile Devices

Building recognition from images and video streams of mobile devices to texturize and refine an existing 3D city model is an open challenge, since such models most often do not completely represent the actual buildings. We present ways to extract buildings from images enabling improvement of the existing model. The approach is based on edge detection on images to detect walls, pure use of sensor data by creating an overlay to the video stream with the 3D model renderer from current position by a server, and the use of structure from motion algorithms to create point clouds and recognize a building via the support of the device's sensors. We show that we are thus able to texturize and refine an existing 3D city model.