Background modeling is a technique for extracting moving objects in video frames. This technique can be used in machine vision applications, such as video frame compression and monitoring. To model the background in video frames, initially, a model of scene background is constructed, then the current frame is subtracted from the background. Eventually, the difference determines the moving objec...

Abstract A large number of modern video background modeling algorithms deal with computational costly minimization problems that often need parameter adjustments. While in most cases spatial and temporal constraints are added artificially to the process, our approach is exploit Dynamic Mode Decomposition (DMD), a spectral decomposition technique naturally extracts spatio-temporal patterns from ...

Background modeling is an important step in moving object detection and tracking. In this paper, we propose a new statistical approach in which, a sequence of frames are selected according to velocity and direction of some moving objects and then an initial background is modeled, based on the detection of gray pixel's value changes. To have used this sequence of frames, no estimator or distribu...