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首页> 外文期刊>Neural Networks: The Official Journal of the International Neural Network Society >On the road to invariant object recognition: how cortical area V2 transforms absolute to relative disparity during 3D vision.
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On the road to invariant object recognition: how cortical area V2 transforms absolute to relative disparity during 3D vision.

机译:在不变物体识别的道路上:皮质区域V2如何在3D视觉期间将绝对视差转换为相对视差。

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摘要

Invariant recognition of objects depends on a hierarchy of cortical stages that build invariance gradually. Binocular disparity computations are a key part of this transformation. Cortical area V1 computes absolute disparity, which is the horizontal difference in retinal location of an image in the left and right foveas. Many cells in cortical area V2 compute relative disparity, which is the difference in absolute disparity of two visible features. Relative, but not absolute, disparity is invariant under both a disparity change across a scene and vergence eye movements. A neural network model is introduced which predicts that shunting lateral inhibition of disparity-sensitive layer 4 cells in V2 causes a peak shift in cell responses that transforms absolute disparity from V1 into relative disparity in V2. This inhibitory circuit has previously been implicated in contrast gain control, divisive normalization, selection of perceptual groupings, and attentional focusing. The model hereby links relative disparity to other visual functions and thereby suggests new ways to test its mechanistic basis. Other brain circuits are reviewed wherein lateral inhibition causes a peak shift that influences behavioral responses.
机译:对象的不变识别取决于逐渐形成不变的皮质阶段的层次。双目视差计算是此转换的关键部分。皮质区域V1计算绝对视差,即视差在左,右中央凹中视网膜位置的水平差。皮质区域V2中的许多单元计算相对视差,这是两个可见特征的绝对视差的差。相对(但不是绝对)的视差在场景中的视差变化和发散的眼球运动中都是不变的。引入了一个神经网络模型,该模型预测对V2中的视差敏感第4层细胞进行分流横向抑制会导致细胞响应发生峰移动,从而将绝对视差从V1转换为V2中的相对视差。该抑制电路先前与对比度增益控制,分割归一化,感知分组的选择和注意力集中有关。该模型在此将相对差异与其他视觉功能联系起来,从而提出了测试其机械基础的新方法。审查了其他大脑回路,其中侧向抑制导致影响行为反应的峰移动。

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