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» PCA in Autocorrelation Space
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CVPR
2003
IEEE
14 years 9 months ago
Constrained Subspace Modelling
When performing subspace modelling of data using Principal Component Analysis (PCA) it may be desirable to constrain certain directions to be more meaningful in the context of the...
Jaco Vermaak, Patrick Pérez
CVPR
2004
IEEE
14 years 9 months ago
Visual Tracking Using Learned Linear Subspaces
This paper presents a simple but robust visual tracking algorithm based on representing the appearances of objects using affine warps of learned linear subspaces of the image spac...
Jeffrey Ho, Kuang-Chih Lee, Ming-Hsuan Yang, David...
CVPR
2005
IEEE
14 years 9 months ago
Hallucinating Faces: TensorPatch Super-Resolution and Coupled Residue Compensation
In this paper, we propose a new face hallucination framework based on image patches, which integrates two novel statistical super-resolution models. Considering that image patches...
Wei Liu, Dahua Lin, Xiaoou Tang
CVPR
2007
IEEE
14 years 9 months ago
Robust Estimation of Texture Flow via Dense Feature Sampling
Texture flow estimation is a valuable step in a variety of vision related tasks, including texture analysis, image segmentation, shape-from-texture and texture remapping. This pap...
Yu-Wing Tai, Michael S. Brown, Chi-Keung Tang
ICCV
2005
IEEE
14 years 9 months ago
A Multi-Scale Hybrid Linear Model for Lossy Image Representation
This paper introduces a simple and efficient representation for natural images. We partition an image into blocks and treat the blocks as vectors in a high-dimensional space. We t...
Wei Hong, John Wright, Kun Huang, Yi Ma