DocumentCode :
3708123
Title :
T-clustering: Image clustering by tensor decomposition
Author :
Amara Tariq;Hassan Foroosh
Author_Institution :
The Computational Imaging Lab., Computer Science, University of Central Florida, Orlando, FL, USA
fYear :
2015
Firstpage :
4803
Lastpage :
4807
Abstract :
Image clustering is an important tool for organizing evergrowing image repositories for efficient search and retrieval. A variety of clustering algorithms have been employed to cluster images. In this paper, we present a clustering algorithm, named T-Clustering, especially tailored to suit image collections. T-Clustering is based on tensor decomposition and takes into account the spatial configuration of images. This algorithm is non-parametric and works very well with raw images, thus alleviating the need for transformation of images in any feature domain. Our experiments prove that this algorithm outperforms well-known non-parametric clustering algorithms for a variety of image collections.
Keywords :
"Tensile stress","Clustering algorithms","Matrix decomposition","Image databases","Visualization","Yttrium","Manifolds"
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/ICIP.2015.7351719
Filename :
7351719
Link To Document :
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