Title
Grouping Based on Coupled Diffusion Maps
Abstract
Systems of coupled, non-linear diffusion equations are proposed as a computational tool for grouping. Grouping tasks are divided into two classes - local and bilocal - and for each a prototypical set of equations is presented. It is shown how different cues can be used for grouping given these two blueprints plus cue-specific specialisations. Results are shown for intensity, texture orientation, stereo disparity, optical flow, mirror symmetry, and regular textures. The proposed equations are particularly well suited for parallel implementations. They also show some interesting analogies with basic architectural characteristics of the cortex.
Year
DOI
Venue
1999
10.1007/3-540-46805-6_12
Shape, Contour and Grouping in Computer Vision
Keywords
Field
DocType
different cue,proposed equation,cue-specific specialisations,diffusion maps,non-linear diffusion equation,mirror symmetry,interesting analogy,grouping task,computational tool,basic architectural characteristic,optical flow,diffusion equation
Computer vision,Epipolar line,Flow (psychology),Mirror symmetry,Artificial intelligence,Diffusion map,Optical flow,Mathematics,Motion vector
Conference
Volume
ISSN
ISBN
1681
0302-9743
3-540-66722-9
Citations 
PageRank 
References 
3
0.45
4
Authors
2
Name
Order
Citations
PageRank
Marc Proesmans127734.37
Luc Van Gool2275661819.51