Next Article in Journal
Superconducting Gap Symmetry of LaFeP(O,F) Observed by Impurity Doping Effect
Next Article in Special Issue
The Conformal Camera in Modeling Active Binocular Vision
Previous Article in Journal
Automatic Frequency Identification under Sample Loss in Sinusoidal Pulse Width Modulation Signals Using an Iterative Autocorrelation Algorithm
Previous Article in Special Issue
Relationship between Fractal Dimension and Spectral Scaling Decay Rate in Computer-Generated Fractals
Open AccessArticle

Modeling Bottom-Up Visual Attention Using Dihedral Group D4

Department of Engineering & Safety (IIS-IVT), UiT-The Arctic University of Norway, Tromsø-9037, Norway
This paper is an extended version of my paper published in 11th International Symposium on Visual Computing (ISVC 2015).
Academic Editors: Marco Bertamini and Lewis Griffin
Symmetry 2016, 8(8), 79;
Received: 27 April 2016 / Revised: 19 July 2016 / Accepted: 9 August 2016 / Published: 15 August 2016
(This article belongs to the Special Issue Symmetry in Vision)
In this paper, first, we briefly describe the dihedral group D 4 that serves as the basis for calculating saliency in our proposed model. Second, our saliency model makes two major changes in a latest state-of-the-art model known as group-based asymmetry. First, based on the properties of the dihedral group D 4 , we simplify the asymmetry calculations associated with the measurement of saliency. This results is an algorithm that reduces the number of calculations by at least half that makes it the fastest among the six best algorithms used in this research article. Second, in order to maximize the information across different chromatic and multi-resolution features, the color image space is de-correlated. We evaluate our algorithm against 10 state-of-the-art saliency models. Our results show that by using optimal parameters for a given dataset, our proposed model can outperform the best saliency algorithm in the literature. However, as the differences among the (few) best saliency models are small, we would like to suggest that our proposed model is among the best and the fastest among the best. Finally, as a part of future work, we suggest that our proposed approach on saliency can be extended to include three-dimensional image data. View Full-Text
Keywords: image analysis; saliency image analysis; saliency
Show Figures

Figure 1

MDPI and ACS Style

Sharma, P. Modeling Bottom-Up Visual Attention Using Dihedral Group D4. Symmetry 2016, 8, 79.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop