Paper Info
Title
Shape Gradients for Histogram Segmentation using Active Contours
Abstract
We consider the problem of image segmentation using active contoursthrough the minimization of an energy criterion involving bothregion and boundary functionals. These functionals are derivedthrough a shape derivative approach instead of classical calculusof variation. The equations can be elegantly derived withoutconverting the region integrals into boundary integrals. From thederivative, we deduce the evolution equation of an active contourthat makes it evolve towards a minimum of the criterion. We focusmore particularly on statistical features globally attached to theregion and especially to the probability density functions of imagefeatures such as the color histogram of a region. A theoreticalframework is set for the minimization of the distance between twohistograms for matching or tracking purposes. An application ofthis framework to the segmentation of color histograms in videosequences is then proposed. We briefly describe our numericalscheme and show some experimental results.
Year
DOI
Venue
2003
10.1109/ICCV.2003.1238375
ICCV
Keywords
Field
DocType
histogram segmentation,application ofthis framework,boundary functionals,color histogram,region integral,shape gradients,active contoursthrough,active contours,classical calculusof variation,energy criterion,active contourthat,boundary integral,image segmentation,active contour,image features,partial differential equations,minimisation,calculus of variation,probability density function,minimization
Active contour model,Histogram,Pattern recognition,Color histogram,Computer science,Feature (computer vision),Segmentation,Calculus of variations,Image segmentation,Region growing,Artificial intelligence
Conference
ISBN
Citations 
PageRank 
0-7695-1950-4
28
2.36
References 
Authors
11
4
Name
Order
Citations
PageRank
Stéphanie Jehan-Besson127718.54
Michel Barlaud22317310.53
Gilles Aubert31275108.17
Olivier D. Faugeras493642568.69