A parametric spectral model for texture-based salience
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.
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 conference
Publication
Pattern Recognition
ISSN
0302-9743Type
Conference item
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.