An improved total variation regularized RPCA for moving object detection with dynamic background | Zendy

Xianchao Xiu | Zendy; Ying Yang | Zendy; Wanquan Liu | Zendy; Lingchen Kong | Zendy; Meijuan Shang | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

An improved total variation regularized RPCA for moving object detection with dynamic background

Author(s) -

Xianchao Xiu,

Ying Yang,

Wanquan Liu,

Lingchen Kong,

Meijuan Shang

Publication year - 2019

Publication title -

journal of industrial and management optimization

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.325

H-Index - 32

eISSN - 1553-166X

pISSN - 1547-5816

DOI - 10.3934/jimo.2019024

Subject(s) - robust principal component analysis , computer science , singular value decomposition , principal component analysis , variation (astronomy) , matrix norm , exploit , rank (graph theory) , computation , foreground detection , singular value , sparse approximation , sparse matrix , artificial intelligence , curse of dimensionality , pattern recognition (psychology) , object detection , algorithm , mathematics , gaussian , physics , computer security , eigenvalues and eigenvectors , quantum mechanics , combinatorics , astrophysics

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research