Linear Multi View Reconstruction with Missing Data

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Linear Multi View Reconstruction with Missing Data
General multi view reconstruction from affine or projective cameras has so far been solved most efficiently using methods of factorizing image data matrices into camera and scene parameters. This can be done directly for affine cameras [18] and after computing epipolar geometry for projective cameras [17]. A notorious problem has been the fact that these factorization methods require all points to be visible in all views. This paper presents alternative algorithms for general affine and projective views of multiple points where a) points and camera centers are computed as the nullspace of one linear system constructed from all the image data b) only three points have to be visible in all views. The latter requirement increases the flexibility and usefulness of 3D reconstruction from multiple views. In the case of projective views and unknown epipolar geometry, an additional algorithm is presented which initially assumes affine views and compensates iteratively for the perspective effec...
Carsten Rother, Stefan Carlsson
Added 16 Oct 2009
Updated 16 Oct 2009
Type Conference
Year 2002
Where ECCV
Authors Carsten Rother, Stefan Carlsson
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