# Differential Matching Constraints

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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Conference papers

https://hal.inria.fr/inria-00548310
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Triggs-dmc-iccv99.pdf
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### Citation

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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