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
AbstractLarge 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)
Media
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},
}
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