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Direct estimation of affine image deformations using visual front-end operations with automatic scale selection
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0002-9081-2170
1995 (English)In: Proc. 5th International Conference on Computer Vision: ICCV'95 (Boston, MA), IEEE Computer Society, 1995, 134-141 p.Conference paper (Refereed)
Abstract [en]

This article deals with the problem of estimating deformations of brightness patterns using visual front-end operations. Estimating such deformations constitutes an important subtask in several computer vision problems relating to image correspondence and shape estimation. The following subjects are treated: The problem of decomposing affine flow fields into simpler components is analysed in detail. A canonical parametrization is presented based on singular value decomposition, which naturally separates the rotationally invariant components of the flow field from the rotationally variant ones. A novel mechanism is presented for automatic selection of scale levels when estimating local affine deformations. This mechanism is expressed within a multi-scale framework where disparity estimates are computed in a hierarchical coarse-to-fine manner and corrected using iterative techniques. Then, deformation estimates are selected from the scales that minimize a certain normalized residual over scales. Finally, the descriptors so obtained serve as initial data for computing refined estimates of the local deformations.

Place, publisher, year, edition, pages
IEEE Computer Society, 1995. 134-141 p.
Keyword [en]
affine transformation, scale selection, image correspondence, optic flow, shape estimation, stereo, motion, texture, disparity, vergence, invariance, deformation, decomposition, singular value, second moment matrix, surface model, enforced consistency, visual front-end, scale-space, computer vision
National Category
Computer Science Computer Vision and Robotics (Autonomous Systems)
URN: urn:nbn:se:kth:diva-58611DOI: 10.1109/ICCV.1995.466795OAI: diva2:473428
5th International Conference on Computer Vision

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Available from: 2013-04-19 Created: 2012-01-05 Last updated: 2013-04-19Bibliographically approved

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