Skip to main navigation Skip to search Skip to main content

Closed-form solutions to image flow equations for 3D structure and motion

  • University of Maryland, College Park

Research output: Contribution to journalArticlepeer-review

51 Scopus citations

Abstract

A major source of three-dimensional (3D) information about objects in the world is available to the observer in the form of time-varying imagery. Relative motion between textured objects and the observer generates a time-varying optic array at the image, from which image motion of contours, edge fragments, and feature points can be extracted. These dynamic features serve to sample the underlying "image flow" field. New, closed-form solutions are given for the structure and motion of planar and curved surface patches from monocular image flow and its derivatives through second order. Both planar and curved surface solutions require at most, the solution of a cubic equation. The analytic solution for curved surface patches combines the transformation of Longuet-Higgins and Prazdny [25] with the planar surface solution of Subbarao and Waxman [43]. New insights regarding uniqueness of solutions also emerge. Thus, the "structure-motion coincidence" of Waxman and Ullman [54] is interpreted as the "duality of tangent plane solutions." The multiplicity of transformation angles (up to three) is related to the sign of the Gaussian curvature of the surface patch. Ovoid patches (i.e., bowls) are shown to possess a unique transform angle, though they are subject to the local structure-motion coincidence. Thus, ovoid patches almost always yield a unique 3D interpretation. In general, ambiguous solutions can be resolved by requiring continuity of the solution over time.

Original languageEnglish
Pages (from-to)239-258
Number of pages20
JournalInternational Journal of Computer Vision
Volume1
Issue number3
DOIs
StatePublished - Oct 1988

Fingerprint

Dive into the research topics of 'Closed-form solutions to image flow equations for 3D structure and motion'. Together they form a unique fingerprint.

Cite this