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Symmetry 2016, 8(8), 79; https://doi.org/10.3390/sym8080079

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
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)
Full-Text   |   PDF [1019 KB, uploaded 19 August 2016]   |  

Abstract

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

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