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首页> 外文期刊>Neural Networks: The Official Journal of the International Neural Network Society >A neural model of selective attention and object segmentation in the visual scene: an approach based on partial synchronization and star-like architecture of connections.
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A neural model of selective attention and object segmentation in the visual scene: an approach based on partial synchronization and star-like architecture of connections.

机译：视觉场景中选择性注意和对象分割的神经模型：一种基于部分同步和星形连接结构的方法。

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摘要

A brain-inspired computational system is presented that allows sequential selection and processing of objects from a visual scene. The system is comprised of three modules. The selective attention module is designed as a network of spiking neurons of the Hodgkin-Huxley type with star-like connections between the central unit and peripheral elements. The attention focus is represented by those peripheral neurons that generate spikes synchronously with the central neuron while the activity of other peripheral neurons is suppressed. Such dynamics corresponds to the partial synchronization mode. It is shown that peripheral neurons with higher firing rates are preferentially drawn into partial synchronization. We show that local excitatory connections facilitate synchronization, while local inhibitory connections help distinguishing between two groups of peripheral neurons with similar intrinsic frequencies. The module automatically scans a visual scene and sequentially selects regions of interest for detailed processing and object segmentation. The contour extraction module implements standard image processing algorithms for contour extraction. The module computes raw contours of objects accompanied by noise and some spurious inclusions. At the next stage, the object segmentation module designed as a network of phase oscillators is used for precise determination of object boundaries and noise suppression. This module has a star-like architecture of connections. The segmented object is represented by a group of peripheral oscillators working in the regime of partial synchronization with the central oscillator. The functioning of each module is illustrated by an example of processing of the visual scene taken from a visual stream of a robot camera.
机译：提出了一种灵感来自大脑的计算系统，该系统允许从视觉场景中顺序选择和处理对象。该系统由三个模块组成。选择性注意模块被设计为霍奇金-赫克斯利型尖峰神经元的网络，中央单元与外围元件之间具有星形连接。注意焦点由那些与中枢神经元同步产生尖峰而抑制其他周围神经元活动的外周神经元代表。这种动力学对应于部分同步模式。结果表明，具有较高放电率的周围神经元优先被引入部分同步。我们表明，局部兴奋性连接促进同步，而局部抑制性连接则有助于区分具有相似固有频率的两组周围神经元。该模块自动扫描视觉场景，并顺序选择感兴趣的区域以进​​行详细处理和对象分割。轮廓提取模块实现用于轮廓提取的标准图像处理算法。该模块可计算出带有噪声和一些虚假夹杂物的物体的原始轮廓。在下一阶段，被设计为相位振荡器网络的目标分割模块用于精确确定目标边界和抑制噪声。该模块具有星形连接结构。分段的对象由一组工作在与中央振荡器部分同步的状态下的外围振荡器组成。通过从机器人摄像机的视觉流中获取的视觉场景的处理示例来说明每个模块的功能。

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