Domain Adaptive Subspace Clustering

Mahdi Abavisani and Vishal Patel

Abstract

We propose domain adaptive extensions of the recently introduced sparse subspace clustering and low-rank representation-based subspace clustering algorithms for clustering data lying in a union of subspaces. We propose a general method that learns the projections of data in a space where the sparsity or low-rankness of data is maintained. We propose an efficient iterative procedure for solving the proposed optimization problems. Various experiments on face, object and handwritten digits datasets show that the proposed methods can perform better than many competitive subspace clustering methods.

Session

Posters 2

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DOI

10.5244/C.30.126
https://dx.doi.org/10.5244/C.30.126

Citation

Mahdi Abavisani and Vishal Patel. Domain Adaptive Subspace Clustering. In Richard C. Wilson, Edwin R. Hancock and William A. P. Smith, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 126.1-126.12. BMVA Press, September 2016.

Bibtex

        @inproceedings{BMVC2016_126,
        	title={Domain Adaptive Subspace Clustering},
        	author={Mahdi Abavisani and Vishal Patel},
        	year={2016},
        	month={September},
        	pages={126.1-126.12},
        	articleno={126},
        	numpages={12},
        	booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
        	publisher={BMVA Press},
        	editor={Richard C. Wilson, Edwin R. Hancock and William A. P. Smith},
        	doi={10.5244/C.30.126},
        	isbn={1-901725-59-6},
        	url={https://dx.doi.org/10.5244/C.30.126}
        }