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» On sparse signal representations
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ICCV
2011
IEEE
14 years 6 months ago
Blurring-Invariant Riemannian Metrics for Comparing Signals and Images
We propose a novel Riemannian framework for comparing signals and images in a manner that is invariant to their levels of blur. This framework uses a log-Fourier representation of...
Zhengwu Zhang, Eric Klassen, Anuj Srivastava, Pava...
CORR
2012
Springer
163views Education» more  CORR 2012»
14 years 2 months ago
The Structure of Signals: Causal Interdependence Models for Games of Incomplete Information
Traditional economic models typically treat private information, or signals, as generated from some underlying state. Recent work has explicated alternative models, where signals ...
Michael P. Wellman, Lu Hong, Scott E. Page
CVPR
2005
IEEE
16 years 8 months ago
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
Robert Fergus, Pietro Perona, Andrew Zisserman
ICCV
2005
IEEE
16 years 8 months ago
Sparse Image Coding Using a 3D Non-Negative Tensor Factorization
We introduce an algorithm for a non-negative 3D tensor factorization for the purpose of establishing a local parts feature decomposition from an object class of images. In the pas...
Tamir Hazan, Simon Polak, Amnon Shashua
ICCV
2001
IEEE
16 years 8 months ago
Determining Reflectance Parameters and Illumination Distribution from a Sparse Set of Images for View-dependent Image Synthesis
A framework for photo-realistic view-dependent image synthesis of a shiny object from a sparse set of images and a geometric model is proposed. Each image is aligned with the 3D m...
Ko Nishino, Zhengyou Zhang, Katsushi Ikeuchi