Video object segmentation based on change detection and frame difference accumulation

In order to solve the problems such as the inaccuracy of the segmentation contour extraction, occlusion, and irregular motion in video object segmentation methods, a novel video object segmentation method is proposed. Based on the human visual characteristics that human are sensitive to motion (temporal gradient) and edge (spatial gradient) especially, the inter frame motion change detection (the accumulation of fixed temporal interval frames difference) and image edge detection are combined to segment moving objects from stationary background precisely. First, t-distribution significance test is used to detect the inter frame changes of symmetrical frames;Second, the accumulation of fixed temporal interval frames difference of the detected initial motion change region is calculated, and then it can be integrated to form the movement memory template;Third, an improved Kirsch edge detection operator is used to detect all the edge information in current frame accurately;Fourth, spatial-temporal filter is used to reduce the residual noises in memory template and extract the semantic video object plane;Fifth, the video objects segmentation can be obtained finally by applying filling and morphology operation selectively. By comparing our experimental results with other popular algorithms', the results indicate the validity and accuracy of the proposed algorithm.