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» Learning Image Components for Object Recognition
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119
Voted
PAMI
2002
114views more  PAMI 2002»
15 years 2 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
141
Voted
CVPR
2004
IEEE
16 years 4 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
NIPS
1997
15 years 4 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 3 months 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...
130
Voted
CVPR
2007
IEEE
16 years 4 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