ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5, 9-16, 2014
https://doi.org/10.5194/isprsannals-II-5-9-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
28 May 2014
Visibility analysis of point cloud in close range photogrammetry
B. Alsadik1,2, M. Gerke1, and G. Vosselman1 1University of Twente, ITC Faculty, EOS department, Enschede, The Netherlands
2University of Baghdad, College of Engineering, Surveying Department, Baghdad, Iraq
Keywords: Visibility, point cloud, voxel, HPR , line tracing, z buffering Abstract. The ongoing development of advanced techniques in photogrammetry, computer vision (CV), robotics and laser scanning to efficiently acquire three dimensional geometric data offer new possibilities for many applications. The output of these techniques in the digital form is often a sparse or dense point cloud describing the 3D shape of an object. Viewing these point clouds in a computerized digital environment holds a difficulty in displaying the visible points of the object from a given viewpoint rather than the hidden points. This visibility problem is a major computer graphics topic and has been solved previously by using different mathematical techniques. However, to our knowledge, there is no study of presenting the different visibility analysis methods of point clouds from a photogrammetric viewpoint. The visibility approaches, which are surface based or voxel based, and the hidden point removal (HPR) will be presented. Three different problems in close range photogrammetry are presented: camera network design, guidance with synthetic images and the gap detection in a point cloud. The latter one introduces also a new concept of gap classification. Every problem utilizes a different visibility technique to show the valuable effect of visibility analysis on the final solution.
Conference paper (PDF, 1693 KB)


Citation: Alsadik, B., Gerke, M., and Vosselman, G.: Visibility analysis of point cloud in close range photogrammetry, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5, 9-16, https://doi.org/10.5194/isprsannals-II-5-9-2014, 2014.

BibTeX EndNote Reference Manager XML