Implementation of the template model of vision.

Abstract

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.