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Differential Matching Constraints

Bill Triggs 1
1 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Graphisme, Vision et Robotique, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : We introduce a finite difference expansion for closely spaced cameras in projective vision, and use it to derive differential analogues of the finite-displacement projective matching tensors and constraints. The results are simpler, more general and easier to use than Astrom & Heyden's time-derivative based `continuous time matching constraints'. We suggest how to use the formalism for `tensor tracking'-propagation of matching relations against a fixed base image along an image sequence. We relate this to non-linear tensor estimators and show how `unwrapping the optimization loop' along the sequence allows simple `linear n point' update estimates to converge rapidly to statistically near-optimal, near-consistent tensor estimates as the sequence proceeds. We also give guidelines as to when difference expansion is likely to be worthwhile as compared to a discrete approach.
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https://hal.inria.fr/inria-00548310
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Submitted on : Monday, December 20, 2010 - 8:43:10 AM
Last modification on : Friday, June 26, 2020 - 4:04:03 PM
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Bill Triggs. Differential Matching Constraints. 7th International Conference on Computer Vision (ICCV '99), Sep 1999, Kerkyra, Greece. pp.370--376, ⟨10.1109/ICCV.1999.791244⟩. ⟨inria-00548310⟩

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