Decomposition into low-rank plus additive matrices for background/foreground separation: A review for a comparative evaluation with a large-scale dataset.
Thierry BouwmansAndrews SobralSajid JavedSoon Ki JungEl-Hadi ZahzahPublished in: Comput. Sci. Rev. (2017)
Keyphrases
- comparative evaluation
- low rank
- matrix completion
- low rank matrix
- singular value decomposition
- background foreground
- data matrix
- singular values
- matrix decomposition
- matrix factorization
- missing data
- convex optimization
- linear combination
- low rank and sparse
- low rank approximation
- tensor decomposition
- low rank matrices
- high dimensional data
- binary matrix
- affinity matrix
- high order
- semi supervised
- nonnegative matrix factorization
- dimensionality reduction
- sparse matrix
- collaborative filtering
- least squares
- object recognition