A New Linear Method for Euclidean Motion/Structure from Three Calibrated Affine Views

  • Authors:
  • L. Quan;Y. Ohta

  • Affiliations:
  • -;-

  • Venue:
  • CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
  • Year:
  • 1998

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Abstract

We introduce a unified framework for developing matching constraints of multiple affine views and rederive 2-view (affine epipolar geometry) and 3-view (affine image transfer) constraints within this framwork. We then describe a new linear method for Euclidean motion and structure from 3 calibrated affine images, based on insight into the particular structure of these multiple-view constraints.Compared with the existing linear method of Huang and Lee [7], the new method uses different and more appropriate constraints. It has no failure mode of the Euclidean factorisation method of Tomasi and Kanade [18]. We demonstrate the method on real image sequences.