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» Learning the 2-D Topology of Images
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ECCV
2000
Springer
14 years 11 months ago
Learning to Recognize 3D Objects with SNoW
This paper describes a novel view-based learning algorithm for 3D object recognition from 2D images using a network of linear units. The SNoW learning architecture is a sparse netw...
Ming-Hsuan Yang, Dan Roth, Narendra Ahuja
CVIU
2006
166views more  CVIU 2006»
13 years 10 months ago
Non-parametric and light-field deformable models
Statistical shape-and-texture appearance models use image morphing to define a rich, compact representation of object appearance. They are useful in a variety of applications incl...
Chris Mario Christoudias, Louis-Philippe Morency, ...
CVPR
2005
IEEE
14 years 12 months ago
Coupled Kernel-Based Subspace Learning
It was prescriptive that an image matrix was transformed into a vector before the kernel-based subspace learning. In this paper, we take the Kernel Discriminant Analysis (KDA) alg...
Shuicheng Yan, Dong Xu, Lei Zhang, Benyu Zhang, Ho...
SMI
2005
IEEE
14 years 3 months ago
Mesh Editing with an Embedded Network of Curves
We propose a new topological data structure for representing a set of polygonal curves embedded in a meshed surface. In this embedding, the vertices of the curve do not necessaril...
Wan-Chiu Li, Bruno Lévy, Jean-Claude Paul
FGR
2008
IEEE
346views Biometrics» more  FGR 2008»
14 years 4 months ago
Markov random field models for hair and face segmentation
This paper presents an algorithm for measuring hair and face appearance in 2D images. Our approach starts by using learned mixture models of color and location information to sugg...
Kuang-chih Lee, Dragomir Anguelov, Baris Sumengen,...