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» Unsupervised Learning of Invariant Features Using Video
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SLSFS
2005
Springer
14 years 1 months ago
Constructing Visual Models with a Latent Space Approach
We propose the use of latent space models applied to local invariant features for object classification. We investigate whether using latent space models enables to learn patterns...
Florent Monay, Pedro Quelhas, Daniel Gatica-Perez,...
FGR
2000
IEEE
112views Biometrics» more  FGR 2000»
14 years 1 days ago
Viewpoint-Invariant Learning and Detection of Human Heads
We present a method to learn models of human heads for the purpose of detection from different viewing angles. We focus on a model where objects are represented as constellations ...
Markus Weber, Wolfgang Einhäuser, Max Welling...
CVPR
2009
IEEE
15 years 1 months ago
Learning Signs from Subtitles: A Weakly Supervised Approach to Sign Language Recognition
This paper introduces a fully-automated, unsupervised method to recognise sign from subtitles. It does this by using data mining to align correspondences in sections of videos. Bas...
Helen Cooper, Richard Bowden
ICANN
2010
Springer
13 years 8 months ago
A Bilinear Model for Consistent Topographic Representations
Visual recognition faces the difficult problem of recognizing objects despite the multitude of their appearances. Ample neuroscientific evidence shows that the cortex uses a topogr...
Urs Bergmann, Christoph von der Malsburg
ICML
2003
IEEE
14 years 8 months ago
Unsupervised Learning with Permuted Data
We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
Sergey Kirshner, Sridevi Parise, Padhraic Smyth