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Selective Visual Attention: Computational Models and Applications by Weisi Lin, Liming Zhang

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5.3 Computational Model under Top-down Influence

As stated earlier, it is not very clear how top-down knowledge is represented and how visual attention is influenced by top-down knowledge in the brain. However, many psychophysical experiments have validated that the subject's motivation and experience stored in their brain often speed up finishing the task such as target search and recognition, scene understanding and so on. Attention modelling under the influence of a task is proposed in [14], which is related to the representation of top-down knowledge, task-specific guidance for visual attention, and object recognition under the guidance of top-down knowledge. This model combines top-down and bottom-up attention together to find salient locations in a scene for object detection, and object recognition at these salient locations via the prior knowledge of the relevance between the object and current task. The prior knowledge in [14] is stored in working memory and long-term memory in two potential forms. One is symbolic representation – the task defined by subject and task-relevance of existing objects – that is regarded as human inherent knowledge and their current motivation. The other is low-level features related to the expected object (statistical properties for each low-level feature) that need to be learned from many instances. The stored low-level features are regarded as the knowledge about a subject's experience. Both potential forms of the prior knowledge guide the ...

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