Information

Abstract

This paper introduces a concept for automatic focusing on features within a volumetric data set. The user selects a focus, i.e., object of interest, from a set of pre-defined features. Our system automatically determines the most expressive view on this feature. An optimal viewpoint is estimated by a novel information-theoretic framework which is based on mutual information measure. Viewpoints change smoothly by switching the focus from one feature to another one. This mechanism is controlled by changes in the importance distribution among features in the volume. The highest importance is assigned to the feature in focus. Apart from viewpoint selection, the focusing mechanism also steers visual emphasis by assigning a visually more prominent representation. To allow a clear view on features that are normally occluded by other parts of the volume, the focusing also incorporates cut-away views.

Additional Files and Images

Additional images and videos

image1: hand - arteria radialis image1: hand - arteria radialis
image2: hand - arteria ulnaris image2: hand - arteria ulnaris
image3: hand - radius image3: hand - radius
image4: stag beetle - legs image4: stag beetle - legs
image5: torso - bones image5: torso - bones
image6: torso - intestine image6: torso - intestine
image7: torso - kidneys image7: torso - kidneys
image8: torso - liver image8: torso - liver
image9: torso - vessels image9: torso - vessels
video: visual presentation of hand data set video: visual presentation of hand data set

Additional files

pdf: technical report pdf file pdf: technical report pdf file

Weblinks

No further information available.

BibTeX

@techreport{TR-186-2-06-02,
  title =      "Importance-Driven Focus of Attention",
  author =     "Ivan Viola and Miquel Feixas and Mateu Sbert and Eduard
               Gr\"{o}ller",
  year =       "2006",
  abstract =   "This paper introduces a concept for automatic focusing on
               features within a volumetric data set. The user selects a
               focus, i.e., object of interest, from a set of pre-defined
               features. Our system automatically determines the most
               expressive view on this feature. An optimal viewpoint is
               estimated by a novel information-theoretic framework which
               is based on mutual information measure. Viewpoints change
               smoothly by switching the focus from one feature to another
               one. This mechanism is controlled by changes in the
               importance distribution among features in the volume. The
               highest importance is assigned to the feature in focus.
               Apart from viewpoint selection, the focusing mechanism also
               steers visual emphasis by assigning a visually more
               prominent representation. To allow a clear view on features
               that are normally occluded by other parts of the volume, the
               focusing also incorporates cut-away views.",
  month =      apr,
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  institution = "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  note =       "human contact: technical-report@cg.tuwien.ac.at",
  keywords =   "optimal viewpoint estimation, interacting with volumetric
               datasets, volume visualization, illustrative visualization,
               focus+context techniques",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2006/TR-186-2-06-02/",
}