Abstract
We present a novel saliency mechanism based on texture. Local texture at each pixel is characterised by the 2D spectrum obtained from oriented Gabor filters. We then apply a parametric model and describe the texture at each pixel by a combination of two 1D Gaussian approximations. This results in a simple model which consists of only four parameters. These four parameters are then used as feature channels and standard Difference-of-Gaussian blob detection is applied in order to detect salient areas in the image, similar to the Itti and Koch model. Finally, a diffusion process is used to sharpen the resulting regions. Evaluation on a large saliency dataset shows a significant improvement of our method over the baseline Itti and Koch model.
Original language | English |
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Title of host publication | Pattern Recognition |
Subtitle of host publication | 37th German Conference, GCPR 2015, Aachen, Germany, October 7-10, 2015, Proceedings |
Editors | Juergen Gall, Peter Gehler, Bastian Leibe |
Place of Publication | Cham |
Publisher | Springer |
Pages | 331-342 |
Number of pages | 12 |
ISBN (Electronic) | 9783319249476 |
ISBN (Print) | 9783319249469 |
DOIs | |
Publication status | Published - 2015 |
Event | 37th German Conference on Pattern Recognition, GCPR 2015 - Aachen, Germany Duration: 7 Oct 2015 → 10 Oct 2015 Conference number: 37 http://gcpr2015.rwth-aachen.de/ |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 9358 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 37th German Conference on Pattern Recognition, GCPR 2015 |
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Abbreviated title | GCPR |
Country/Territory | Germany |
City | Aachen |
Period | 7/10/15 → 10/10/15 |
Internet address |