An efficient video object segmentation scheme

In this paper, two new algorithms have been proposed for performing video object segmentation. In both algorithms, a new method has been proposed for adaptive threshold estimation for the change detection process. The method is able to provide a reliable estimation of the threshold without knowing explicitly which data corresponds to the moving and non-moving elements in the video sequence. In addition, the use of new specially detected “moving” edgels and also a graph-based edge-linking method that employs both gradient-based and edge-based constraints have also been proposed in order to refine the object segmentation mask. The second algorithm further incorporates an initialisation phase to solve the problems of dis-occluded regions appearing as part of the segmented moving objects. The proposed work has shown a reasonably fast and good video object segmentation technique that operates in real-time and can be applied in applications such as MPEG-4´s content-based video coding and home/office/warehouse security. Comparison with one of the MPEG-4 adopted video object segmentation techniques shows that our approach is very significantly faster and yet produces better results.