Background Subtraction via Fast Robust Matrix Completion

  title={Background Subtraction via Fast Robust Matrix Completion},
  author={Behnaz Rezaei and S. Ostadabbas},
  journal={2017 IEEE International Conference on Computer Vision Workshops (ICCVW)},
  • Behnaz Rezaei, S. Ostadabbas
  • Published 2017
  • Computer Science, Engineering
  • 2017 IEEE International Conference on Computer Vision Workshops (ICCVW)
  • Background subtraction is the primary task of the majority of video inspection systems. The most important part of the background subtraction which is common among different algorithms is background modeling. In this regard, our paper addresses the problem of background modeling in a computationally efficient way, which is important for current eruption of "big data" processing coming from high resolution multi-channel videos. Our model is based on the assumption that background in natural… CONTINUE READING
    12 Citations
    Moving Object Detection Through Robust Matrix Completion Augmented With Objectness
    • 8
    G-LBM: Generative Low-dimensional Background Model Estimation from Video Sequences
    • 1
    • PDF
    Low Rank and Sparse Decomposition of Ultrasound Color Flow Images for Suppressing Clutter in Real-Time
    • 5
    • PDF
    Complete Moving Object Detection in the Context of Robust Subspace Learning
    • 1
    • PDF
    Suppressing Clutter Components In Ultrasound Color Flow Imaging Using Robust Matrix Completion Algorithm: Simulation And Phantom Study
    • 4
    • Highly Influenced
    Moving Objects Detection with a Moving Camera: A Comprehensive Review
    • 3
    • PDF
    Automatic collateral circulation scoring in ischemic stroke using 4D CT angiography with low-rank and sparse matrix decomposition
    • 2
    • Highly Influenced


    Comparison of Matrix Completion Algorithms for Background Initialization in Videos
    • 27
    • PDF
    Video background subtraction using semi-supervised robust matrix completion
    • Hassan Mansour, A. Vetro
    • Mathematics, Computer Science
    • 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
    • 2014
    • 29
    • PDF
    Incremental gradient on the Grassmannian for online foreground and background separation in subsampled video
    • 324
    • Highly Influential
    • PDF
    Moving Object Detection by Detecting Contiguous Outliers in the Low-Rank Representation
    • 504
    • Highly Influential
    • PDF
    A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos
    • 510
    Adaptive background mixture models for real-time tracking
    • C. Stauffer, W. Grimson
    • Computer Science
    • Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)
    • 1999
    • 7,316
    • PDF
    The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrices
    • 2,028
    • PDF
    Robust principal component analysis?
    • 4,934
    • PDF