视觉信息获取中基于对象的选择性视觉注意机制的计算模型

Tianfu Wu, Jun Gao, Qin Zhao
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引用次数: 18

摘要

介绍了一种基于对象的选择性视觉注意计算模型。选择性注意的单位是什么,永远是选择性注意的焦点。现有的选择性注意计算模型大多是基于空间的,但越来越多的神经科学实验表明它是基于对象的。对于基于对象的注意来说,如何定义“对象”是最大的难点,一般认为“对象”是指格式塔规则创造的“感知对象”。然而,格式塔规则很难在图像中计算。本文提出的模型由两个独立的部分组成。其中一个部分是利用感知颜色线索进行基于对象的分割,另一个部分是利用返回抑制机制生成基于对象的显著性图。最后,通过实验验证了该模型的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A computational model of object-based selective visual attention mechanism in visual information acquisition
A computational model of object-based selective visual attention is introduced. What are the units of selective attention is always the focus of selective attention. Most existing computational model of selective attention is space-based, but more and more neuroscience experiments indicate that it is object-based. For object-based attention, how to define "object" is the biggest difficulty and it is generally accepted that the "object" refers to "perceptual object" which is created by Gestalt rules. However, Gestalt rules are very difficult to be calculated in images. The model presented in this paper is comprised of two independent components. One component is object-based segmentation by using perceptual color cues, the other is the generation of a object-based saliency-map in terms of the inhibition of return mechanism. Lastly, the results of experiments show that the model is valid.
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