Sajid Javed

Learn More
Background/foreground separation is the first step in video surveillance system to detect moving objects. Recent research on problem formulations based on decomposition into low-rank plus sparse matrices shows a suitable framework to separate moving objects from the background. The most representative problem formulation is the Robust Principal Component(More)
Background modeling and foreground object detection is the first step in visual surveillance system. The task becomes more difficult when the background scene contains significant variations, such as water surface, waving trees and sudden illumination conditions, etc. Recently, subspace learning model such as <i>Robust Principal Component Analysis</i>(More)
Accurate and efficient foreground detection is an important task in video surveillance system. The task becomes more critical when the background scene shows more variations, such as water surface, waving trees, varying illumination conditions, etc. Recently, Robust Principal Components Analysis (RPCA) shows a very nice framework for moving object(More)
Accurate and efficient background subtraction is an important task in video surveillance system. The task becomes more critical when the background scene shows more variations, such as water surface, waving trees and lighting conditions, etc. Recently, Robust Principal Components Analysis (RPCA) shows a nice framework for moving object detection. The(More)