Ongoing Research
Contour Extraction based on Geometric Consistency
We present a framework for extracting image contours based on geometric and structural consistency among edge element locations and orientations.
We consider all discrete n-tuples of edgels in a local neighborhood (7x7) and retain those that are geometrically consistent with a local second-order (circular arc) or third-order (Euler-spiral) curve model. This results in a number of ordered discrete combinations of edgels, each represented by a bundle of curves (see animation).
The resulting curve bundle map is a representation of all
possible local groupings from which longer contour fragments are constructed.
Publication:
No Grouping Left Behind: From Edges to Curve Fragments, A. Tamrakar and B. B.
Kimia. In Proceedings of the Eleventh IEEE International Conference on Computer
Vision, Rio de Janeiro, Brazil, October 2007. [PDF][Poster].
Medial Visual Fragments Representation for Image Segmentation and Perceptual Organization
We present a novel representation of images based on a decomposition into atomic patches which we call medial visual
fragments and which is particularly suited for structural grouping. Specifically, we show that the medial
axis/shock graph of a contour map partitions the image domain into non-overlapping regions, which together with the
image information define the visual fragments.
The main advantage of such a generic representation is that both contour and regional information are explicitly available so that in the presence of partial evidence and ambiguity in maps indicating edges and regional homogeneity, both aspects can be simultaneously used for perceptual grouping of fragments into a coherent whole. Grouping of visual fragments is implemented as a set of canonical transformations of visual fragments, namely, the gap and loop transforms.
The following animation demonstrates the visual fragment transformations during perceptual grouping of a donut behind an occluder.
Publication:
Medial Visual Fragments as an Intermediate Image Representation for Segmentation and
Perceptual grouping, A. Tamrakar and B. B. Kimia. In Proceedings of the 2004 Conference
on Computer Vision and Pattern Recognition Workshop on Perceptual Organization in
Computer Vision, Washington D.C., p. 47. [PDF][PPT].
Contour-Based Edge Cue Integration for Robust Contour Detection
