Selective Visual Attention: Computational Models and Applications

2.2 Feature Integration Theory (FIT) of Visual Attention

As introduced in Section 2.1, input stimuli projected on the retina are processed through the LGN, primary cortex V1, V2 until the high cortex in the HVS. The RFs of some neurons in the LGN are the centre-surround homocentric circle that extracts objects edges on their RFs, while other cells with colour-opponent RFs in the LGN extract colour features. In the V1 area there are simple cells with different orientation-selective and colour-antagonistic RF to select respective features of input stimuli. Some simple cells in V1 have frequency sensitivity. The neurons at higher layer have larger RF size which can obtain more complex features or a large number of features. Detective cells for motion direction in the LGN and V1 can perceive movement of objects. Since these neurons in the early cortex work simultaneously, we know that the perception of these features in the input scene is done in parallel. Then perceptive information is further processed through the dorsal and ventral streams in different brain areas. However, how to search an object with several different features in the intricate visual input and how to bind the separate features dispersed in diverse cortical regions together to a specific object in the human vision, are not clear only from the viewpoint of either physiology or anatomy.

Many psychologists and experts on neuroscience have engaged in the feature binding problem for more than three decades [29–34]. ...