Robust Matrix Completion (RMC)
This work aims to investigate the background model initialization as a matrix completion problem. Thus, we consider the image sequence (or video) as a partially observed matrix. First, a simple joint motiondetection and frame-selection operation is done. The redundant frames are eliminated, and the moving regions are represented by zeros in our observation matrix. The second stage involves evaluating nine popular matrix completion algorithms with the Scene Background Initialization (SBI) data set, and analyze them with respect to the background model challenges. The experimental results shows the good performance of LRGeomCG method over its direct competitors. (more information)
A. Sobral, T. Bouwmans, E. Zahzah, "Comparison of Matrix Completion Algorithms for Background Initialization in Videos”, SBMI 2015 Workshop in conjunction with ICIAP 2015, Genova, Italy, September 2015.
Spatio-temporal Low-rank Matrix Completion (SLMC)
This work presents a spatio-temporal low-rank modeling method on dynamic video clips for estimating the robust background model. The proposed method encodes spatio-temporal constraints by regularizing spectral graphs. Initially a motion-compensated binary matrix is generated using optical flow information to remove redundant data and to create a set of dynamic frames from the input video sequence. Then two graphs are constructed, one between frames for temporal consistency and the other between features for spatial consistency, to encode the local structure for continuously promoting the intrinsic behavior of the low-rank model against outliers. These two terms are then incorporated in the iterative matrix completion framework for improved segmentation of background. Rigorous evaluation on severely occluded and dynamic background sequences, demonstrates the superior performance of the proposed method over state-of-the art approaches. (more information)
S. Javed, A. Mahmood, T. Bouwmans, S. Jung, “Spatiotemporal Low-rank Modeling for Complex Scene Background Initialization", IEEE Transactions on Circuits and Systems for Video Technology, November 2016.
S. Javed, S. Jung, A. Mahmood, T. Bouwmans, "Motion-Aware Graph Regularized RPCA for Background Modeling of Complex Scenes", Scene Background Modeling Contest, International Conference on Pattern Recognition, ICPR 2016, December 2016.