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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,我们将从模拟人类视觉系统中的视觉信息操纵过程的角度提供视觉显着性建模的见解。对于人类来说,视觉刺激会被视网膜转换成尖峰序列,然后将尖峰信号传输到大脑区域进行进一步分析。因此,我们建议基于视网膜神经网络来估计图像显着性,该网络是用真实的形态学和电物理数据构建的。然后,我们分析了视网膜产生的尖峰序列与图像显着性之间的相关性。实验结果表明,视网膜尖峰序列在图像显着性分析中是有效的。

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