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A parametric spectral model for texture-based salience
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dc.contributor.author | Terzić, Kasim | |
dc.contributor.author | Krishna, Sai | |
dc.contributor.author | Du Buf, J. M.H. | |
dc.contributor.editor | Gall, Juergen | |
dc.contributor.editor | Gehler, Peter | |
dc.contributor.editor | Leibe, Bastian | |
dc.date.accessioned | 2018-09-04T11:30:05Z | |
dc.date.available | 2018-09-04T11:30:05Z | |
dc.date.issued | 2015 | |
dc.identifier | 255500533 | |
dc.identifier | d19955de-fbce-4b83-bbf8-d88bde7d9c65 | |
dc.identifier | 84952359587 | |
dc.identifier.citation | Terzić , K , Krishna , S & Du Buf , J M H 2015 , A parametric spectral model for texture-based salience . in J Gall , P Gehler & B Leibe (eds) , Pattern Recognition : 37th German Conference, GCPR 2015, Aachen, Germany, October 7-10, 2015, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 9358 , Springer , Cham , pp. 331-342 , 37th German Conference on Pattern Recognition, GCPR 2015 , Aachen , North Rhine-Westphalia , Germany , 7/10/15 . https://doi.org/10.1007/978-3-319-24947-6_27 | en |
dc.identifier.citation | conference | en |
dc.identifier.isbn | 9783319249469 | |
dc.identifier.isbn | 9783319249476 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.uri | https://hdl.handle.net/10023/15957 | |
dc.description.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. | |
dc.format.extent | 12 | |
dc.format.extent | 3378885 | |
dc.language.iso | eng | |
dc.publisher | Springer | |
dc.relation.ispartof | Pattern Recognition | en |
dc.relation.ispartofseries | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | T Technology | en |
dc.subject | Computer Science(all) | en |
dc.subject | Theoretical Computer Science | en |
dc.subject | NDAS | en |
dc.subject.lcc | QA75 | en |
dc.subject.lcc | T | en |
dc.title | A parametric spectral model for texture-based salience | en |
dc.type | Conference item | en |
dc.contributor.institution | University of St Andrews. School of Computer Science | en |
dc.identifier.doi | 10.1007/978-3-319-24947-6_27 |
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