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CVPR
2003
IEEE
14 years 7 months ago
Generalized Principal Component Analysis (GPCA)
This paper presents an algebro-geometric solution to the problem of segmenting an unknown number of subspaces of unknown and varying dimensions from sample data points. We represen...
René Vidal, Shankar Sastry, Yi Ma
KDD
2004
ACM
216views Data Mining» more  KDD 2004»
14 years 5 months ago
GPCA: an efficient dimension reduction scheme for image compression and retrieval
Recent years have witnessed a dramatic increase in the quantity of image data collected, due to advances in fields such as medical imaging, reconnaissance, surveillance, astronomy...
Jieping Ye, Ravi Janardan, Qi Li
ICIP
2004
IEEE
14 years 6 months ago
Sparse representation of images with hybrid linear models
We propose a mixture of multiple linear models, also known as hybrid linear model, for a sparse representation of an image. This is a generalization of the conventional KarhunenLo...
Kun Huang, Allen Y. Yang, Yi Ma
ECCV
2006
Springer
13 years 8 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
ICIP
2005
IEEE
14 years 6 months ago
Segmenting small regions in the presence of noise
Binary segmentation, a problem of extracting foreground objects from the background, often arises in medical imaging and document processing. Popular existing solutions include Ex...
Rashi Samur, Vitali Zagorodnov