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CVPR
2003
IEEE
16 years 9 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman
CVPR
2005
IEEE
16 years 9 months ago
Generative versus Discriminative Methods for Object Recognition
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the di...
Ilkay Ulusoy, Christopher M. Bishop
CVPR
2008
IEEE
16 years 9 months ago
Photometric stereo with non-parametric and spatially-varying reflectance
We present a method for simultaneously recovering shape and spatially varying reflectance of a surface from photometric stereo images. The distinguishing feature of our approach i...
Neil G. Alldrin, Todd Zickler, David J. Kriegman
ICCV
2003
IEEE
16 years 9 months ago
Real Time Pattern Matching Using Projection Kernels
A novel approach to pattern matching is presented, which reduces time complexity by two orders of magnitude compared to traditional approaches. The suggested approach uses an effi...
Yacov Hel-Or, Hagit Hel-Or
ECCV
2008
Springer
16 years 9 months ago
Kernel Codebooks for Scene Categorization
This paper introduces a method for scene categorization by modeling ambiguity in the popular codebook approach. The codebook approach describes an image as a bag of discrete visual...
Jan van Gemert, Jan-Mark Geusebroek, Cor J. Veenma...