Departmental Papers (CIS)

Date of this Version

December 2007

Document Type

Journal Article

Comments

Postprint version. Published in International Journal of Computer Vision, Volume 75, Issue 3, December 2007, pages 311-327.
Publisher URL: http://dx.doi.org/10.1007/s11263-007-0035-2

Abstract

We present a novel approach for the estimation of 3D-motion directly from two images using the Radon transform. The feasibility of any camera motion is computed by integrating over all feature pairs that satisfy the epipolar constraint. This integration is equivalent to taking the inner product of a similarity function on feature pairs with a Dirac function embedding the epipolar constraint. The maxima in this five dimensional motion space will correspond to compatible rigid motions. The main novelty is in the realization that the Radon transform is a filtering operator: If we assume that the similarity and Dirac functions are defined on spheres and the epipolar constraint is a group action of rotations on spheres, then the Radon transform is a correlation integral. We propose a new algorithm to compute this integral from the spherical Fourier transform of the similarity and Dirac functions. Generating the similarity function now becomes a preprocessing step which reduces the complexity of the Radon computation by a factor equal to the number of feature pairs processed. The strength of the algorithm is in avoiding a commitment to correspondences, thus being robust to erroneous feature detection, outliers, and multiple motions.

Keywords

motion estimation, structure from motion, registration, harmonic analysis, correspondence-free motion

Share

COinS
 

Date Posted: 26 October 2007

This document has been peer reviewed.