Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/108967
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Type: | Conference paper |
Title: | Null space clustering with applications to motion segmentation and face clustering |
Author: | Ji, P. Zhong, Y. Li, H. Salzamn, M. |
Citation: | Proceedings / ICIP ... International Conference on Image Processing, 2014, pp.283-287 |
Publisher: | IEEE |
Issue Date: | 2014 |
ISBN: | 978-1-4799-5751-4 |
ISSN: | 1522-4880 2381-8549 |
Conference Name: | 2014 IEEE International Conference on Image Processing (ICIP 2014) (27 Oct 2014 - 30 Oct 2014 : Paris, France) |
Statement of Responsibility: | Pan Ji, Yiran Zhong, Hongdong Li, Mathieu Salzmann |
Abstract: | The problems of motion segmentation and face clustering can be addressed in a framework of subspace clustering methods. In this paper, we tackle the more general problem of clustering data points lying in a union of low-dimensional linear(or affine) subspaces, which can be naturally applied in motion segmentation and face clustering. For data points drawn from linear (or affine) subspaces, we propose a novel algorithm called Null Space Clustering (NSC), utilizing the null space of the data matrix to construct the affinity matrix. To better deal with noise and outliers, it is converted to an equivalent problem with Frobenius norm minimization, which can be solved efficiently. We demonstrate that the proposed NSC leads to improved performance in terms of clustering accuracy and efficiency when compared to state-of-the-art algorithms on two well-known datasets, i.e., Hopkins 155 and Extended Yale B. |
Keywords: | Null space, subspace clustering, affinity matrix, normalized cuts, motion segmentation, face clustering |
Rights: | © 2014 IEEE |
DOI: | 10.1109/ICIP.2014.7025056 |
Grant ID: | http://purl.org/au-research/grants/arc/DP120103896 http://purl.org/au-research/grants/arc/DP130104567 http://purl.org/au-research/grants/arc/LP100100588 http://purl.org/au-research/grants/arc/CE140100016 |
Published version: | http://dx.doi.org/10.1109/icip.2014.7025056 |
Appears in Collections: | Aurora harvest 8 Computer Science publications |
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