Moving object Segmentation; using optical flow with active contour model

The paper presents an object segmentation approach that combines optical flow and active contour model to characterize objects and follow them in video sequences. Our aims is to discriminate moving objects from a static background. The approach is based on a minimization of a functional of energy (E) which uses perceptual information in regions of interest (ROI) in an image, in conjunction with a mixture of Gaussian to model voxels of the background image and those of the visual objects. In this work, we compute the optical flow then we use the result of the optical flow as an input in an active contour model. Experiments with a number of test sequences are promising and extend the numerous works on this subject.