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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
Conference Name: 2014 IEEE International Conference on Image Processing (ICIP 2014) (27 Oct 2014 - 30 Oct 2014 : Paris, France)
Statement of
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
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