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We introduce a method to texture 3D urban models with photographs that even works for Google Streetview images and can be donewith currently available free software. This allows realistic texturing, even when it is not possible or cost-effective to (re)visit a scannedsite to take textured scans or photographs. Mapping a photograph onto a 3D model requires knowledge of the intrinsic and extrinsiccamera parameters. The common way to obtain intrinsic parameters of a camera is by taking several photographs of a calibrationobject with a priori known structure. The extra challenge of using images from a database such as Google Streetview, rather thanyour own photographs, is that it does not allow for any controlled calibration. To overcome this limitation, we propose to calibratethe panoramic viewer of Google Streetview using Structure from Motion (SfM) on any structure of which Google Streetview offersviews from multiple angles. After this, the extrinsic parameters for any other view can be calculated from 3 or more tie points betweenthe image from Google Streetview and a 3D model of the scene. These point correspondences can either be obtained automatically orselected by manual annotation. We demonstrate how this procedure provides realistic 3D urban models in an easy and effective way,by using it to texture a publicly available point cloud from a terrestrial laser scan made in Bremen, Germany, with a screenshot fromGoogle Streetview, after estimating the focal length from views from Paris, France

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

A SEMI-AUTOMATIC PROCEDURE FOR TEXTURING OF LASER SCANNING POINT CLOUDS WITH GOOGLE STREETVIEW IMAGES