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24 January 2012A unified method for comparison of algorithms of saliency extraction
Extracting salient regions of a still image, which are pertinent areas likely to attract subjects' fixations, can be useful to
adapt compression loss according to human attention. In the literature, various algorithms have been proposed for
saliency extraction, ranging from region-of-interest (ROI) or point-of-interest (POI) algorithms to saliency models,
which also extract ROIs. Implementing such an algorithm within image sensors implies to evaluate its complexity and
performance of fixation prediction. However, there have been no pertinent criteria to compare these algorithms in
predicting human fixations due to the different nature between ROIs and POIs. In this paper, we propose a novel
criterion which is able to compare the prediction performance of ROI and POI algorithms. Aiming at the electronic
implementation of such an algorithm, the proposed criterion is based on blocks, which is consistent with processing
within image sensors. It also takes into account salient surface, an important factor in electronic implementation, to
reflect more accurately the prediction performance of algorithms. The criterion is then used for comparison in a
benchmark of several saliency models and ROI/POI algorithms. The results show that a saliency model, which has
higher computational complexity, gives better performance than other ROI/POI algorithms.
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Tien Ho-Phuoc, Laurent Alacoque, Antoine Dupret, Anne Guérin-Dugué, Arnaud Verdant, "A unified method for comparison of algorithms of saliency extraction," Proc. SPIE 8293, Image Quality and System Performance IX, 829315 (24 January 2012); https://doi.org/10.1117/12.908681