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由底向上视觉注意中的层次性数据竞争

Hierarchical Data Competition in the Bottom-Up Visual Attention System

  • 摘要: 结合认知心理学的相关发现,研究了由底向上视觉注意中的数据竞争问题,提出了一个新的基于层次竞争的视觉注意模型.该模型采用依次进行的尺度、特征和方位竞争逐渐搜索注意焦点的基本属性,利用区域生长简单描述注意焦点的大致轮廓,并通过上述过程的循环往复逐一获得图像中的各个注意焦点.将此方法应用于多种类型的真实图像中获得了较为满意的实验结果.

     

    Abstract: In this paper, inspired by the findings in cognition psychology, we study the data competition in the bottom-up visual attention system and bring up a novel visual attention model based on the hierarchical competition. By this model, the competitions of scale, feature and location are applied hierarchically to define the fundamental attributes of the focus of attention (FOA), and then the method of region growth is employed to describe the contour of the FOA. In this way, every FOA with different properties in an image is detected in series. We apply the model to various real images, and the exciting outcome shows that the model is effective.

     

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