Detection of depth in binocular visual systems using Kuramoto models

Wenxue Wang, B. Ghosh
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Abstract

Animals routinely rely on their eyes to localize fixed and moving targets especially with the goal of either avoiding or capturing them. Detection of position of targets in space is an important problem in such a localization process for the motor control circuit to actuate a successful movement. The purpose of this paper is to sketch a binocular visual system that includes image capturing, retinal projection, sparse representation and data fusion, multi-neural encoding in the cortex down to detection of depth of objects from activity waves using nonlinear dynamics of an oscillatory network. The general strategies from visual circuitry, some of which may not be employed by the animal, could perhaps be employed in building machines with multiple sensors
基于Kuramoto模型的双目视觉系统深度检测
动物通常依靠它们的眼睛来定位固定和移动的目标,尤其是在躲避或捕捉目标时。在这种定位过程中,目标在空间中的位置检测是电机控制电路成功实现运动的一个重要问题。本文的目的是概述一个双目视觉系统,包括图像捕获,视网膜投影,稀疏表示和数据融合,皮层中的多神经编码,直到使用振荡网络的非线性动力学从活动波中检测物体的深度。视觉回路的一般策略,其中一些可能不被动物采用,也许可以用于制造具有多个传感器的机器
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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