Automatic Texture and Orthophoto Generation From Registered Panoramic Views

Abstract

ABSTRACT:Recent trends in 3D scanning are aimed at the fusion of range data and color information from images. The combination of these two outputs allows to extract novel semantic information. The workflow presented in this paper allows to detect objects, such as light switches, that are hard to identify from range data only. In order to detect these elements, we developed a method that utilizes range data and color information from high-resolution panoramic images of indoor scenes, taken at the scanners position. A proxy geometry is derived from the point clouds; orthographic views of the scene are automatically identified from the geometry and an image per view is created via projection. We combine methods of computer vision to train a classifier to detect the objects of interest from these orthographic views. Furthermore, these views can be used for automatic texturing of the proxy geometry.(a) (b) Figure 1: The data acquisition equipment: For range data acquisition, a Faro Focus 3D Scanner was used (a); additional color information was obtained using a customized adapter connecting the base tripod of the 3D scanner with a HDRI camera (b).

Recognition and Positioning of SBCs in BIM Models Using a Geometric vs Colour Consensus Approach

“…It is assumed that the segmented regions correspond to these objects, so that there is no proper recognition algorithm. Sockets and switches are also recognized in 2D images in [15]. Eruhimov et al ([16]) classify between power holes, ground holes and the background in images acquired by a mobile robot.…”

A Survey of Algorithmic Shapes

“…Furthermore, the surface appearance has to be acquired [114]. In the case of building interiors, the generation of orthographic images can be used for surface color representation and the retrieval of additional semantic information [115]. Such semantic relationships have to be acquired and represented within the model [116]; see also the foregoing section about semantic enrichment.…”

Development of a New Low-Cost Indoor Mapping System – System Design, System Calibration and First Results

“…Furthermore, so-called depth sensors (time-of-flight cameras) have already been used for the recording of interiors (Zhu & Donia 2013, Henry et al 2014. How semantic information can be automatically extracted from point clouds derived from photography of the interior for BIM applications has been described by Tamke et al (2014) and Krispel et al (2015).…”