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» Learning in Computer Vision: Some Thoughts
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EMMCVPR
2001
Springer
13 years 12 months ago
A Hierarchical Markov Random Field Model for Figure-Ground Segregation
To segregate overlapping objects into depth layers requires the integration of local occlusion cues distributed over the entire image into a global percept. We propose to model thi...
Stella X. Yu, Tai Sing Lee, Takeo Kanade
JMLR
2006
131views more  JMLR 2006»
13 years 7 months ago
On Representing and Generating Kernels by Fuzzy Equivalence Relations
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
Bernhard Moser
FGR
2011
IEEE
271views Biometrics» more  FGR 2011»
12 years 11 months ago
Active conditional models
— Matching images with large geometric and iconic changes (e.g. faces under different poses and facial expressions) is an open research problem in computer vision. There are two ...
Ying Chen, Fernando De la Torre
CVPR
2007
IEEE
14 years 9 months ago
Spatial selection for attentional visual tracking
Long-duration tracking of general targets is quite challenging for computer vision, because in practice target may undergo large uncertainties in its visual appearance and the unc...
Ming Yang, Junsong Yuan, Ying Wu
ICPR
2004
IEEE
14 years 8 months ago
Discriminative Distance Measures for Image Matching
: Significant progress has been made by the computer vision community in recent years along two fronts: (i) developing complex spatial-temporal models for object registration and t...
Tat-Jen Cham, Xi Chen