Similarity-based Exploded Views

Marc Ruiz, Ivan Viola, Imma Boada, Stefan Bruckner, Miquel Feixas, Mateu Sbert

INPROCEEDINGS, Proceedings of 8th International Symposium on Smart Graphics, Aug, 2008

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Abstract

Exploded views are often used in illustration to overcome the problem of occlusion when depicting complex structures. In this paper, we propose a volume visualization technique inspired by exploded views that partitions the volume into a number of parallel slabs and shows them apart from each other. The thickness of slabs is driven by the similarity between partitions. We use an information-theoretic technique for the generation of exploded views. First, the algorithm identifies the viewpoint from which the structure is the highest. Then, the partition of the volume into the most informative slabs for exploding is obtained using two complementary similarity-based strategies. The number of slabs and the similarity parameter are freely adjustable by the user.

Published

Proceedings of 8th International Symposium on Smart Graphics

• Pages: 154–165
• Location: Rennes, France
• Date: Aug 2008
• Project: Illustrative Visualization, MedViz
• URL: http://www.cg.tuwien.ac.at/research/publications/2008/ruiz-2008-SEV/

Media

BibTeX

@inproceedings{ruiz08similarity,
  title = {Similarity-based Exploded Views},
  author = {Marc Ruiz and Ivan Viola and Imma Boada and Stefan Bruckner and Miquel Feixas and Mateu Sbert}, 
  year = {2008},
  pages = {154--165},
  month = {Aug},
  booktitle = {Proceedings of 8th International Symposium on Smart Graphics},
  location = {Rennes, France},
  abstract = {Exploded views are often used in illustration to overcome the problem of occlusion when depicting complex structures. In this paper, we propose a volume visualization technique inspired by exploded views that partitions the volume into a number of parallel slabs and shows them apart from each other. The thickness of slabs is driven by the similarity between partitions. We use an information-theoretic technique for the generation of exploded views. First, the algorithm identifies the viewpoint from which the structure is the highest. Then, the partition of the volume into the most informative slabs for exploding is obtained using two complementary similarity-based strategies. The number of slabs and the similarity parameter are freely adjustable by the user.},
  URL = {http://www.cg.tuwien.ac.at/research/publications/2008/ruiz-2008-SEV/},  

}