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Image Saliency Analysis Based on Retina Simulation

机译:基于视网膜仿真的图像显着性分析

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In this paper, we provide an insight of visual saliency modeling from the perspective of simulating visual information manipulation process in human vision system. For humans, visual stimuli are converted into spike trains by retina, and the spike signals are then transferred to brain areas for further analysis. Therefore, we propose to estimate image saliency based on a retina neural network, which is built with realistic morphology and electrophysics data. Then, we analyze the correlation between the spike trains generated by retina and image saliency. The experimental results show the effectiveness of retinal spike trains in image saliency analysis.
机译:在本文中,我们从人体视觉系统中的视觉信息操纵过程的角度提供了对视觉显着建模的洞察。对于人类来说,视觉刺激通过视网膜转化为尖峰列车,然后将尖峰信号转移到脑区域以进行进一步分析。因此,我们建议基于视网膜神经网络来估计图像显着性,其以现实的形态和电物质数据构建。然后,我们分析视网膜和图像显着性产生的尖峰列车之间的相关性。实验结果表明了视网膜尖峰训练在图像显着性分析中的有效性。

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