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» Robust Principal Component Analysis for Computer Vision
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ICCV
1995
IEEE
13 years 11 months ago
Object Indexing Using an Iconic Sparse Distributed Memory
A general-purpose object indexingtechnique is described that combines the virtues of principal component analysis with the favorable matching properties of high-dimensional spaces...
Rajesh P. N. Rao, Dana H. Ballard
ICIP
2008
IEEE
14 years 9 months ago
Principal Component Analysis of spectral coefficients for mesh watermarking
This paper proposes a new robust 3-D object blind watermarking method using constraints in the spectral domain. Mesh watermarking in spectral domain has the property of spreading ...
Ming Luo, Adrian G. Bors
GLOBECOM
2009
IEEE
14 years 2 months ago
Data Acquisition through Joint Compressive Sensing and Principal Component Analysis
—In this paper we look at the problem of accurately reconstructing distributed signals through the collection of a small number of samples at a data gathering point. The techniqu...
Riccardo Masiero, Giorgio Quer, Daniele Munaretto,...
CVPR
2004
IEEE
14 years 9 months ago
A Rao-Blackwellized Particle Filter for EigenTracking
Subspace representations have been a popular way to model appearance in computer vision. In Jepson and Black's influential paper on EigenTracking, they were successfully appl...
Zia Khan, Tucker R. Balch, Frank Dellaert
ECCV
2006
Springer
13 years 11 months ago
Spatial Segmentation of Temporal Texture Using Mixture Linear Models
In this paper we propose a novel approach for the spatial segmentation of video sequences containing multiple temporal textures. This work is based on the notion that a single tem...
Lee Cooper, Jun Liu, Kun Huang