7 citations · 18 across the 8 of their papers we have counts for
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3 papers · 1 filter
math.OC2017★ 4 cited
Weighted Low Rank Approximation for Background Estimation Problems
Aritra Dutta, Xin Li
Classical principal component analysis (PCA) is not robust to the presence of sparse outliers in the data. The use of the norm in the Robust PCA (RPCA) method successfully…
cs.CV2017★ 3 cited
A Batch-Incremental Video Background Estimation Model using Weighted Low-Rank Approximation of Matrices
Aritra Dutta, Xin Li, Peter Richtárik
Principal component pursuit (PCP) is a state-of-the-art approach for background estimation problems. Due to their higher computational cost, PCP algorithms, such as robust principa…
math.OC2017★ 2 cited
A Fast Algorithm for a Weighted Low Rank Approximation
Aritra Dutta, Xin Li
Matrix low rank approximation including the classical PCA and the robust PCA (RPCA) method have been applied to solve the background modeling problem in video analysis. Recently, i…