Abstract
In this paper, we propose a saliency model that 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 which reduces the number of calculations by at-least half that makes it the fastest among the six best algorithms used in this paper. 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 data-set 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 fast GBA model is among the best and the fastest among the best.
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Sharma, P., Eiksund, O. (2015). Group Based Asymmetry–A Fast Saliency Algorithm. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9474. Springer, Cham. https://doi.org/10.1007/978-3-319-27857-5_80
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DOI: https://doi.org/10.1007/978-3-319-27857-5_80
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