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Large Image Collections---Comprehension and Familiarization by Interactive Visual Analysis

Kresimir Matkovic, Denis Gra\vcanin, Wolfgang Freiler, Jana Banova, Helwig Hauser

INPROCEEDINGS, Proceedings of the 10th International Symposium on Smart Graphics (SG'09), 2009

Abstract

Large size and complex multi-dimensional characteristics of image collections demand a multifaceted approach to exploration and analysis providing better comprehension and appreciation. We explore large and complex data-sets composed of images and parameters describing the images. We describe a novel approach providing new and exciting opportunities for the exploration and understanding of such data-sets. We utilize coordinated, multiple views for interactive visual analysis of all parameters. Besides iterative refinement and drill-down in the image parameters space, exploring such data-sets requires a different approach since visual content cannot be completely parameterized. We simultaneously brush the visual content and the image parameter values. The user provides a visual hint (using an image) for brushing in addition to providing a complete image parameters specification. We illustrate our approach on a data-set of more than 26,000 images from Flickr. The developed approach can be used in many application areas, including sociology, marketing, or everyday use.

Published

Proceedings of the 10th International Symposium on Smart Graphics (SG'09)

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BibTeX

@inproceedings{matkovic09imagecollection,
 author = {Kresimir Matkovic and Denis Gra\v{c}anin and 
 	Wolfgang Freiler and Jana Banova and Helwig Hauser},
 title = {Large Image Collections---Comprehension and Familiarization by Interactive Visual Analysis},
 booktitle = {Proceedings of the 10th International Symposium on Smart Graphics (SG'09)},
 year = {2009},
 pages = {15--26},
 publisher = {Springer-Verlag},
 abstract = {Large size and complex multi-dimensional characteristics of image 
collections demand a multifaceted approach to exploration and analysis providing 
better comprehension and appreciation. We explore large and complex data-sets 
composed of images and parameters describing the images. We describe a novel 
approach providing new and exciting opportunities for the exploration and 
understanding of such data-sets. We utilize coordinated, multiple views for 
interactive visual analysis of all parameters. Besides iterative refinement 
and drill-down in the image parameters space, exploring such data-sets requires
a different approach since visual content cannot be completely parameterized. 
We simultaneously brush the visual content and the image parameter values. 
The user provides a visual hint (using an image) for brushing in addition to 
providing a complete image parameters specification. We illustrate our approach 
on a data-set of more than 26,000 images from Flickr. The developed approach can 
be used in many application areas, including sociology, marketing, or everyday use.},

 URL = {http://dx.doi.org/10.1007/978-3-642-02115-2_2},
}






 Last Modified: Jean-Paul Balabanian, 2013-05-29