Adopting principles learnt from insect vision we have constructed model of a general-purpose front-end visual system for motion detection that is designed to operate in parallel along each photoreceptor axis with only local connections. The model is also designed to assist electrophysiological analysis of visual processing because it puts the response to a moving scene into sets of template responses similar to the distribution of activity among different neurons. An earlier template model divided the visual image into the fields of adjacent receptors, measured as intensity or receptor modulation at small increments of time. As soon as we used this model with natural scenes, however, we found that we had to look at changes in intensity, not intensity itself. Running the new model also generated new insights into the effects of very fast motion, of blurring the image, and the value of lateral inhibition. We also experimented with ways of measuring the angular velocity of the image moving across the eye. The camera eye is moved at a known speed and the range to objects is calculated from the angular velocity of contrasts moving across the receptor array. The original template model is modified so that contrast is saturated in a new representation of the original image data. This reduces the 8-bit grey-scale image to a log, 3 = 1.6-bit image, which becomes the input to a look-up table of templates. The output consists of groups of responding templates in specific ratios that define the input features, and these ratios lead into types of invariance at a higher level of further logic. At any stage, there can be persistent parallel inputs from all earlier stages. This design would enable groups of templates to be tuned to different expected situations, such as different velocities, different directions and different types of edges.

中文翻译：

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实现视觉模板模型。

根据从昆虫视觉中学习到的原理，我们构建了用于运动检测的通用前端视觉系统模型，该系统设计为仅通过局部连接即可沿每个感光轴平行运行。该模型还被设计为辅助视觉处理的电生理分析，因为该模型将对运动场景的响应放入类似于不同神经元之间活动分布的模板响应集中。较早的模板模型将视觉图像划分为相邻受体的区域，以较小的时间增量以强度或受体调制进行测量。但是，一旦将此模型用于自然场景，我们便发现必须关注强度的变化，而不是强度本身。运行新模型还产生了对极快运动效果的新见解，图像模糊以及横向抑制的值。我们还尝试了测量穿过眼睛的图像角速度的方法。摄像机的眼睛以已知的速度移动，并且从移动通过接收器阵列的对比度的角速度计算出物体的范围。修改了原始模板模型，以使对比度在原始图像数据的新表示中达到饱和。这样可以将8位灰度图像缩小为对数3 = 1.6位图像，从而成为模板查找表的输入。输出由具有特定比例的响应模板组组成，这些比例定义了输入特征，这些比例导致更高级别的进一步逻辑的不变性类型。在任何阶段，所有早期阶段都可以有持久的并行输入。