This research aims at demonstrating that visual motion analysis can be improved (1) by replacing the analysis of optical flow (the motion of image points) with that of image deformations (their motion relative to each other) and (2) by spanning a wider field of view. The advantages of image deformations are akin to those of differential amplifiers for the detection of weak signals in a noisy background: if noise affects both inputs equally, it is canceled by taking their difference. In the analogy, image motion caused by camera rotation is the noise, and that caused by translation is the useful signal. As to the field of view, the literature shows that a viewing angle of 60 degrees or more leads almost to a quantum improvement in the conditioning of the reconstruction problem. This lead is being pursued by a theoretical and empirical investigation of shape reconstruction from the deformations of wide-angle images induced by camera motion. The two ideas of image deformations and a wide field of view, already proven successful in preliminary studies, are being investigated theoretically and experimentally. The final contribution will be a multiframe shape and motion reconstruction method that works reliably and for perspective images.
