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K Prazdny

Publications and source records attributed to K Prazdny.

22 records · Page 2Linked to original sources

The interpretation of a moving retinal image.

It is shown that from a monocular view of a rigid, textured, curved surface it is possible, in principle, to determine the gradient of the surface at any point, and the motion of the eye relative to it, from the velocity field of the changing retinal image, and its first and second spatial derivatives. The relevant equations are redundant, thus providing a test of the rigidity assumption. They involve, among other observable quantities, the components of shear of the retinal velocity field, suggesting that the visual system may possess specialized channels for computing these components.

Humans↗

Egomotion and relative depth map from optical flow.

When an observer moves in a 3D world, optical flow fields are generated on his retina. We argue that such an observer can in principle compute the parameters of his egomotion, and following this, the relative depth map of the stationary environment solely from the instantaneous positional velocity fields (IPVF). Moreover, we argue that in the stationary world, this analysis can be done locally, and is not dependent on global properties of the optical flow under the imposed ocnstraints (smoothness of the egomotion path, rigidity of objects, temporal continuity of perception). To investigate the method, and to analyze its performance, a computer model has been constructed whch simulates an observer moving through a 3D world of stationary rectangular planes at different depths and orientations. The results suggest that the method offers a reasonable and computationally feasible means of extracting information about egomotion and surface layout from optical flows, under certain circumstances. We discuss some issues related to extending the analysis to the case of a rigid world of moving objects, and some issues related to the status of information extractable from optical flows with respect to other sources of information.

Computers↗