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首页> 外文期刊>Journal of Computers >A Hierarchical Computational Model of Selective Visual Attention
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A Hierarchical Computational Model of Selective Visual Attention

机译：选择性视觉注意的分层计算模型

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Computational model of visual attention has got more and more attention in machine vision and image processing. A hierarchical computational model for selective visual attention is proposed in this paper. This model simulates the attention mechanism from far (coarse) to near (fine) of human visual system. Firstly, the input image is analyzed at the coarsest resolution and visual saliency of each part is computed at this level. Regions of attention are selected according to the saliency. Then the sub-regions of the selected region compete for attention at a finer resolution. This process is done iteratively until every salient region and its sub-regions have been processed at different levels respectively. The proposed model has been tested on many natural images. Experiment results show that the proposed model is valid and the attention results are consistent with human visual system.
机译：视觉注意力的计算模型在机器视觉和图像处理中越来越受到关注。提出了一种选择性视觉注意的分层计算模型。该模型模拟了人类视觉系统从远（粗）到近（精细）的注意力机制。首先，以最粗糙的分辨率分析输入图像，并在此级别上计算每个部分的视觉显着性。根据显着性选择关注区域。然后，所选区域的子区域将以更高的分辨率竞争注意力。反复进行此过程，直到每个显着区域及其子区域分别在不同的级别上进行了处理。建议的模型已在许多自然图像上进行了测试。实验结果表明，该模型是有效的，并且注意结果与人的视觉系统相吻合。

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