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Journal Articles Image and Vision Computing Year : 1997

Linear Projective Reconstruction from Matching Tensors

Abstract

This paper describes initial work on a family of projective reconstruction techniques that compute projection matrices directly and linearly from matching tensors estimated from the image data. The approach is based on “joint image closure relations” — bilinear constraints between matching tensors and projection matrices, that express the fact that the former derive from the latter. The simplest methods use fundamental matrices and epipoles, alternative ones use trilinear tensors. It is possible to treat all of the image data uniformly, without reliance on “privileged” images or tokens. The underlying theory is discussed, and the performance of the new methods is quantified and compared with that of several existing ones.
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Dates and versions

inria-00548357 , version 1 (20-12-2010)

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Bill Triggs. Linear Projective Reconstruction from Matching Tensors. Image and Vision Computing, 1997, 15 (8), pp.617--625. ⟨10.1016/S0262-8856(97)00016-4⟩. ⟨inria-00548357⟩
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