A scale selection principle for estimating image deformations

• A basic functionality of a vision system concerns the ability to compute deformation fields between different images of the same physical structure. This article advocates the need for incorporating explicit mechanisms for scale selection in this context, in algorithms for computing descriptors such as optic flow and for performing stereo matching. A basic reason why such a mechanism is essential is the fact that in a coarse-to-fine propagation of disparity or flow information, it is not necessarily the case that the most accurate estimates are obtained at the finest scales. The existence of interfering structures at fine scales may make it impossible to accurately match the image data at fine scales. selecting deformation estimates from the scales that minimize the (suitably normalized) uncertainty over scales. A specific implementation of this idea is presented for a region based differential flow estimation scheme. It is shown that the integrated scale selection and flow estimation algorithm has the qualitative properties of leading to the selection of coarser scales for larger size image structures and increasing noise level, whereas it leads to the selection of finer scales in the neighbourhood of flow field discontinuities

Subject headings

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

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

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

NATURAL SCIENCES  -- Computer and Information Sciences (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)

art (subject category)