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Selective Attention Guided Perceptual Grouping Model

机译:选择性注意指导的感知分组模型

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摘要

Selective attention works throughout the whole process of vision information processing. Existing attention models concentrate on its role in feature extraction in initial stage, but ignore role of attention in other stages. In this paper, we extend attention to middle stage, especially in guiding perceptual grouping. Selective attention functions in two aspects. One is to select the most salient primitive as grouping seed. The other is to organize groups and decide their pop-out sequence. Compared with traditional attention models, our model judges primitive salience according to global properties rather than local ones. And focus of attention shifts in unit of perceptual object rather than spatial region. These two improvements boost the model's grouping quality and more fit to high stage of vision information processing. Experiments and quantitative analysis testify our model's good performance in certain class of images.
机译:选择性注意在视觉信息处理的整个过程中起作用。现有的注意力模型最初集中于其在特征提取中的作用,而忽略了其他阶段中注意力的作用。在本文中,我们将注意力集中在中间阶段,尤其是在指导感知分组方面。选择性注意在两个方面起作用。一种是选择最明显的图元作为分组种子。另一种是组织组并确定其弹出顺序。与传统注意力模型相比,我们的模型根据全局属性而不是局部属性来判断原始显着性。并且注意力的焦点转移到感知对象的单位而不是空间区域。这两项改进提高了模型的分组质量,更适合视觉信息处理的高级阶段。实验和定量分析证明了我们的模型在某些类别的图像中的良好性能。

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