Recovering depth from stereo-input without using any oculomotor information: A computation model

Journal of Mathematical Psychology. 2021. Vol. 102. Article 102538.

Sawada T.

Human beings can perceive depth by using binocular disparity, namely the difference between a stereo-pair of retinal images. It is commonly believed that the visual system requires oculomotor information about the relative orientation between the two eyes to perceive depth on the basis of binocular disparity. Such oculomotor information can be obtained from the efference copy of the oculomotor signal, or it can be derived from the vertical component of the binocular disparity (vertical disparity). Psychophysical studies have shown that stereo depth perception is affected by both the efference copy and by the vertical disparity. But note that any role for the efference signal for spatial perception is limited and the process using vertical disparity is slow. These effects are too restricted to explain depth perception under natural viewing conditions in which natural eye movements are made. In the present study, I describe a computational model that can recover depth from a stereo-pair of retinal images based only on the geometrical optics. This model treats depth recovery as a Direct problem rather than as an Inverse problem because it does not need to make use of any oculomotor information or of any a priori constraints. In this model, oculomotor information is not even implicitly recovered. Simply put, this paper shows that, at least from a computational perspective, oculomotor information and a priori constraints are not actually required for the stereo perception of depth. Having such a model allows us to discuss psychophysical and neurophysiological phenomena, as well as their mechanisms, without assuming that the human visual system needs oculomotor information to recover depth in a 3D scene from stereo retinal images.

Keywords: 3D perception, projective geometry, 3D видение, multiple view geometry, P3P problem

Publication based on the results of: Visual perception in our everyday life (2019)