Title :
Subspace Clustering
Author_Institution :
He was coeditor of the book Dynamical Vision and has coauthored more than 100 articles in biomedical image analysis, computer vision, machine learning, hybrid systems, and robotics.
fDate :
3/1/2011 12:00:00 AM
Abstract :
Over the past few decades, significant progress has been made in clustering high-dimensional data sets distributed around a collection of linear and affine subspaces. This article presented a review of such progress, which included a number of existing subspace clustering algorithms together with an experimental evaluation on the motion segmentation and face clustering problems in computer vision.
Keywords :
computer vision; face recognition; image motion analysis; image segmentation; pattern clustering; affine subspace; computer vision; face clustering problem; high-dimensional data set clustering; linear subspace; motion segmentation; subspace clustering; Clustering algorithms; Data models; Noise; Polynomials; Principal component analysis; Signal processing algorithms; Subspace constraints;
Journal_Title :
Signal Processing Magazine, IEEE
DOI :
10.1109/MSP.2010.939739
