Data Processing Algorithms for Generating Textured 3D Building Facade Meshes from Laser Scans and Camera Images

Abstract

Abstract. In this paper, we develop a set of data processing algorithms for generating textured facade meshes of cities from a series of vertical 2D surface scans and camera images, obtained by a laser scanner and digital camera while driving on public roads under normal traffic conditions. These processing steps are needed to cope with imperfections and non-idealities inherent in laser scanning systems such as occlusions and reflections from glass surfaces. The data is divided into easy-to-handle quasi-linear segments corresponding to approximately straight driving direction and sequential topological order of vertical laser scans; each segment is then transformed into a depth image. Dominant building structures are detected in the depth images, and points are classified into foreground and background layers. Large holes in the background layer, caused by occlusion from foreground layer objects, are filled in by planar or horizontal interpolation. The depth image is further processed by removing isolated points and filling remaining small holes. The foreground objects also leave holes in the texture of building facades, which are filled by horizontal and vertical interpolation in low frequency regions, or by a copy-paste method otherwise. We apply the above steps to a large set of data of downtown Berkeley with several million 3D points, in order to obtain texture-mapped 3D models.

Dynamic concision for three-dimensional reconstruction of human organ built with virtual reality modelling language (VRML)

“…Although there are many researchers working on PC-based real-time volume rendering recently, such as the shear-warp transform and its variations, as a possible, useful and "new" supplement for traditional methods, in our opinion, direct texture mapping and 3D texture mapping are potentially important ways for medical 3D reconstruction. The involved algorithms will be well and quickly developed in the near future (Frueh et al, 2005).…”

Wide-angle vision for road views

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3d Building Façade Reconstruction Using Handheld Laser Scanning Data

“…Cornelis used essential video frames, then dense matching between stereo frames had done, but in this method building boundary were not be determined and this method just focused on the visualization (Cornelis, 2008). Frueh used depth image that it was obtained from point cloud, then the histograms were plotted in order to distinguish façade points from irrelevant objects, then the façade points were used to generate the TIN mesh models and the texture of photos mapped to models (Frueh, 2005). Pu segmented the building façade points and classified the data to several clusters.…”