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CVPR
2010
IEEE
15 years 6 months ago
Exploring Features in a Bayesian Framework for Material Recognition
We are interested in identifying the material category, e.g. glass, metal, fabric, plastic or wood, from a single image of a surface. Unlike other visual recognition tasks in comp...
Ce Liu, Lavanya Sharan, Edward Adelson, Ruth Rosen...
CVPR
2011
IEEE
14 years 6 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
ICCV
2005
IEEE
15 years 11 months ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona
CVPR
2003
IEEE
15 years 11 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
ICPR
2008
IEEE
15 years 11 months ago
View-invariant full-body gesture recognition from video
In this paper, we propose a video-based full-body gesture recognition system independent of the view angle of the cameras. We performed multilinear analysis on the silhouette imag...
Bo Peng, Gang Qian, Stjepan Rajko