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<p>The inherent ambiguities in recovering 3-D motion information from a single optical flow field are studied using a statistical model. The ambiguities are quantified using the Cramer-Rao lower bound. As a special case, the performance bound for the motion of 3-D rigid planar surfaces is studied in detail. The dependence of the bound on factors such as the underlying motion, surface position, surface orientation, field of view, and density of available pixels are derived as closed-form expressions. A subset of the results support S. Adiv's (1989) analysis of the inherent ambiguities of motion parameters. For the general motion of an arbitrary surface. It is shown that the aperture problem in computing the optical flow restricts the nontrivial information about the 3-D motion to a sparse set of pixels at which both components of the flow velocity are observable. Computer simulations are used to study the dependence of the inherent ambiguities on the underlying motion, the field of view, and the number of feature points for the motion in front of a nonplanar environment.</p>
3D motion recovery; image processing; inherent ambiguities; optical flow field; statistical model; Cramer-Rao lower bound; surface orientation; field of view; aperture; feature points; image processing; optical information processing; statistical analysis

G. Young and R. Chellappa, "Statistical Analysis of Inherent Ambiguities in Recovering 3-D Motion from a Noisy Flow Field," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 14, no. , pp. 995-1013, 1992.
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