Czasopismo | ELEKTRONIKA - KONSTRUKCJE, TECHNOLOGIE, ZASTOSOWANIA | Rocznik 2013 - zeszyt 7

Bottom-up saliency maps - a review

Monika Biskupska

nr katalogowy: 77850

In 1985 the authors Koch and Ullman introduced a concept of a saliency map [1]. It was used to model the human attention and the shifting focus connected with sight and visual stimuli. The saliency map for a given image represents how distinctive the image regions are and in what order the eye and the nervous system process them. In their paper, Koch and Ullman explain that saliency is a measure of difference of the image regions from their surroundings in terms of elementary features such as colour, orientation, movement or distance from the eye. From later works of Koch with Itti and Niebur comes the precise definition: The purpose of the saliency map is to represent the conspicuity - or “saliency" - at every location in the visual field by a scalar quantity and to guide the selection of attended locations, based on the spatial distribution of saliency [2]. Form this concept many algorithms arose working within Koch and Ullman framework. Various methods of selecting and analysing feature maps and then detecting local irregularities of the visual input [3] were designed to produce an accurate and computationally- efficient saliency map, where each pixel is represented by single value indicating its importance. The purpose of this paper is to collect and present the bestknown methods of calculating saliency maps, with an emphasis on bottom-up methods that work without any previous assumptions of the content of processed images. The top-down methods that are designed to work with only a narrow class of images presenting known objects are outside the scope of this review. A model of saliency-based visual attention for rapid scene analysis (Itti/Koch algorithm) [2] Based on the earlier publication of one of the authors [1], it was assumed that it is possible to design an algorithm reflecting the behaviour of the human eye and nervous system while looking at the image. The list of distinguishing features from the previous p[...]

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