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Modelling the Human Visual Process by Evolving Images from Noise

机译:通过从噪声演变图像来建模人类视觉过程

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摘要

The modelling of human visual process is considerably important for developing future autonomous agents such as mobile robots with vision capability. The future efforts will be directed at using this knowledge to develop powerful new algorithms that mimic the human vision capability. In this paper we focus on the process of how the human eye forms an image. We use genetic algorithms to synthetically model this process and interpret the results on different types of objects. In particular, we investigate which of the image properties stabilise early and which ones later, i.e. as the image forms iteratively, does the shape appear before the texture?
机译:人类视觉过程的建模对于开发未来的自治代理(例如具有视觉功能的移动机器人)非常重要。未来的工作将致力于利用这些知识来开发强大的新算法,以模仿人类的视觉能力。在本文中,我们重点关注人眼如何形成图像的过程。我们使用遗传算法对这一过程进行综合建模,并解释不同类型对象的结果。特别是,我们研究了哪些图像属性会较早稳定,而哪些图像属性会稍后稳定,即当图像迭代形成时,形状是否出现在纹理之前?

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