Fast tracking of semantic video object based on motion prediction and subregion extraction

Extraction quality and speed are two fundamental problems for semantic video object extraction. The paper introduces a novel fast-speed tracking algorithm for extracting semantic video objects from image sequences. First, the subregion that covers the contour of a semantic video object is extracted by using motion prediction and mathematical morphology operators to generate the inner and outer contour of the subregion. Then, an optimized tracking scheme is employed to track this particular subregion instead of the whole image. Results on real sequences show that this method greatly improves the processing speed compared to earlier tracking algorithms and that it keeps the quality of the extracted object. Therefore, it is a promising approach for real time processing systems based on video objects.