Focus of Attention and Region Segregation by Low-level Geometry

Research has shown that regions with conspicuous colours are very effective in attracting attention, and that regions with different textures also play an important role. We present a biologically plausible model to obtain a saliency map for Focus-of-Attention (FoA), based on colour and texture boundaries. By applying grouping cells which are devoted to low-level geometry, boundary information can be completed such that segregated regions are obtained. Furthermore, we show that low-level geometry, in addition to rendering filled regions, provides important local cues like corners, bars and blobs for region categorisation. The integration of FoA, region segregation and categorisation is important for developing fast gist vision, i.e., which types of objects are about where in a scene.