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Estimating 3D camera motion without correspondences using a search for the best structure

Summary: Estimating 3D camera motion without correspondences
using a search for the best structure
Faysal Boughorbel *, Paul Crilly, Andreas Koschan, Mongi Abidi
Imaging, Robotics and Intelligent Systems Lab, Electrical and Computer Engineering Department, 409 Ferris Hall,
University of Tennessee, Knoxville, TN 37996, USA
Received 3 December 2001; received in revised form 26 April 2002
A novel approach is presented for recovering the motion parameters of a camera from two frames. The proposed
method does not require establishing point correspondences between the images, as does most current techniques. Our
approach is also more straightforward than the very few non-correspondence motion estimation algorithms. It is based
on the estimation of structure for each given set of motion parameters. This resulting structure is then evaluated in an
optimization process using saliency metrics, until the best structure and motion parameters are obtained. In this work
we have devised and tested two different structure metrics: the first based on scatter and the second using tensor voting.
Experimental results show that this method is effective and can be used in video-based scene modeling systems.
2002 Elsevier Science B.V. All rights reserved.
Keywords: Camera motion; Correspondences; 3D reconstruction; Structure metrics; Scatter; Tensor voting
1. Introduction
The problem of recovering the motion of a
camera from captured image sequences is a fun-
damental problem in computer vision. One of the


Source: Abidi, Mongi A. - Department of Electrical and Computer Engineering, University of Tennessee


Collections: Computer Technologies and Information Sciences