Subspace Segmentation by Low Rank Representation via the Sparse-Prompting Quasi-Rank Function

In this paper, a general optimization formulation is proposed for the subspace segmentation by low rank representation via the sparse-prompting quasi-rank function. We prove that, with the clean data from independent linear subspaces, the optimal solution to our optimization formulation not only is...

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Autori principali:	Haiyang Li, Yusi Wang, Qian Zhang, Zhiwei Xing, Shoujin Lin, Jigen Peng
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	IEEE 2022-01-01
Serie:	IEEE Access
Soggetti:	Band restricted thresholding operator face clustering low rank representation motion segmentation sparse-prompting quasi-rank function subspace segmentation
Accesso online:	https://ieeexplore.ieee.org/document/9775114/
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