Perception and action without veridical metric reconstruction: an affine approach

We present an alternate account of human 3D processing for perception and action. Traditional views postulate that visual mechanisms extract veridical metric properties of environmental objects. Instead, we argue that local affine information, which encodes non metric aspects of a 3D structure, like the depth-order of feature points, determines both our conscious perception of the world and our motor actions. Since only this information is accurately carried on from the earliest stages of 3D processing, our theory predicts large biases in perceptual and motor tasks that require veridical metric estimates. We describe empirical results that support this prediction and show the inadequacy of metric models as computational theories of 3D processing.