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» Learning Image Components for Object Recognition
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PAMI
2002
114views more  PAMI 2002»
14 years 11 months ago
Principal Manifolds and Probabilistic Subspaces for Visual Recognition
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...
Baback Moghaddam
CVPR
2004
IEEE
16 years 1 months ago
Fast, Integrated Person Tracking and Activity Recognition with Plan-View Templates from a Single Stereo Camera
Copyright 2004 IEEE. Published in Conference on Computer Vision and Pattern Recognition (CVPR-2004), June 27 - July 2, 2004, Washington DC. Personal use of this material is permit...
Michael Harville, Dalong Li
98
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NIPS
1997
15 years 1 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
CHI
2009
ACM
16 years 9 days ago
GestureBar: improving the approachability of gesture-based interfaces
GestureBar is a novel, approachable UI for learning gestural interactions that enables a walk-up-and-use experience which is in the same class as standard menu and toolbar interfa...
Andrew Bragdon, Robert C. Zeleznik, Brian Williams...
CVPR
2007
IEEE
16 years 1 months ago
Mapping Natural Image Patches by Explicit and Implicit Manifolds
Image patches are fundamental elements for object modeling and recognition. However, there has not been a panoramic study of the structures of the whole ensemble of natural image ...
Kent Shi, Song Chun Zhu