Efficient dense subspace clustering
-
Altmetric Citations
Ji, Pan; Salzmann, Mathieu; Li, Hongdong
Description
In this paper, we tackle the problem of clustering data points drawn from a union of linear (or affine) subspaces. To this end, we introduce an efficient subspace clustering algorithm that estimates dense connections between the points lying in the same subspace. In particular, instead of following the standard compressive sensing approach, we formulate subspace clustering as a Frobenius norm minimization problem, which inherently yields denser con- nections between the data points. While in...[Show more]
Collections | ANU Research Publications |
---|---|
Date published: | 2014 |
Type: | Conference paper |
URI: | http://hdl.handle.net/1885/74616 |
Source: | 2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014 |
DOI: | 10.1109/WACV.2014.6836065 |
Download
File | Description | Size | Format | Image |
---|---|---|---|---|
01_Ji_Efficient_dense_subspace_2014.pdf | 886.66 kB | Adobe PDF | Request a copy |
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.
Updated: 19 May 2020/ Responsible Officer: University Librarian/ Page Contact: Library Systems & Web Coordinator