Direct estimation of affine image deformations using visual front-end operations with automatic scale selection

• 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.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

Keyword

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

Publication and Content Type

ref (subject category)

kon (subject category)