University of Bergen | Faculty of Mathematics and Natural Sciences | Department of Informatics | Visualization Group
Visualization
You are here: Department of Informatics > Visualization Group > Publications > Pobitzer12Filtering
 Visualization
 > about
 > team & contact info
 > research
 > publications
 > projects
 > teaching
 > seminars
 > resources
 > network
 > events
 > links

Filtering of FTLE for Visualizing Spatial Separation in Unsteady 3D Flow

Armin Pobitzer, Ronald Peikert, Raphael Fuchs, Holger Theisel , Helwig Hauser

INPROCEEDINGS, Topological Methods in Data Analysis and Visualization II, 2012

Abstract

Texture mapping is a common method for combining surface geometry with image data, with the resulting photorealistic 3D models being suitable not only for visualisation purposes but also for interpretation and spatial measurement, in many application fields, such as cultural heritage and the earth sciences. When acquiring images for creation of photorealistic models, it is usual to collect more data than is finally necessary for the texturing process. Images may be collected from multiple locations, sometimes with different cameras or lens configurations and large amounts of overlap may exist. Consequently, much redundancy may be present, requiring sorting to choose the most suitable images to texture the model triangles. This paper presents a framework for visualization and analysis of the geometric relations between triangles of the terrain model and covering image sets. The application provides decision support for selection of an image subset optimized for 3D model texturing purposes, for non-specialists. It aims to improve the communication of geometrical dependencies between model triangles and the available digital images, through the use of static and interactive information visualisation methods. The tool was used for computer-aided selection of image subsets optimized for texturing of 3D geological outcrop models. The resulting textured models were of high quality and with a minimum of missing texture, and the time spent in time-consuming reprocessing was reduced. Anecdotal evidence indicated that an increased user confidence in the final textured model quality and completeness makes the framework highly beneficial.

Published

Topological Methods in Data Analysis and Visualization II

Media

  • paper
  • www
  • Click to view
  • Click to view

BibTeX

@inproceedings{Pobitzer12Filtering,
 author = {Armin Pobitzer and Ronald Peikert and Raphael Fuchs and Holger Theisel
  and Helwig Hauser},
 title = {Filtering of FTLE for Visualizing Spatial Separation in Unsteady 3D Flow},
 booktitle = {Topological Methods in Data Analysis and Visualization II},
 editor = {R. Peikert and H. Hauser and H. Carr and R. Fuchs},
 publisher = {Springer},
 pages = {237--253},
 year = {2012},
  abstract = {Texture mapping is a common method for combining surface geometry with
  image data, with the resulting photorealistic 3D models being suitable not only
  for visualisation purposes but also for interpretation and spatial measurement, 
  in many application fields, such as cultural heritage and the earth sciences. When
  acquiring images for creation of photorealistic models, it is usual to collect more 
  data than is finally necessary for the texturing process. Images may be collected 
  from multiple locations, sometimes with different cameras or lens configurations 
  and large amounts of overlap may exist. Consequently, much redundancy may be present,
  requiring sorting to choose the most suitable images to texture the model triangles. 
  This paper presents a framework for visualization and analysis of the geometric 
  relations between triangles of the terrain model and covering image sets. The 
  application provides decision support for selection of an image subset optimized 
  for 3D model texturing purposes, for non-specialists. It aims to improve the communication 
  of geometrical dependencies between model triangles and the available digital images, 
  through the use of static and interactive information visualisation methods. The 
  tool was used for computer-aided selection of image subsets optimized for texturing 
  of 3D geological outcrop models. The resulting textured models were of high quality 
  and with a minimum of missing texture, and the time spent in time-consuming reprocessing 
  was reduced. Anecdotal evidence indicated that an increased user confidence in the 
  final textured model quality and completeness makes the framework highly beneficial.
 },
 doi = {http://dx.doi.org/10.1007/978-3-642-23175-9_16},
 url = {http://dx.doi.org/10.1007/978-3-642-23175-9_16},

}






 Last Modified: Jean-Paul Balabanian, 2013-11-18