Unsupervised video segmentation based on watersheds and temporal tracking

This paper presents a technique for unsupervised video segmentation. This technique consists of two phases: initial segmentation and temporal tracking, similar to a number of existing techniques. However, new algorithms for spatial segmentation, marker extraction, and modified watershed transformation are proposed for the present technique. The new algorithms make this technique differ from existing techniques by the following features: (1) it can effectively track fast moving objects, (2) it can detect the appearance of new objects as well as the disappearance of existing objects, and (3) it is computationally efficient because of the use of watershed transformations and a fast motion estimation algorithm. Simulation results demonstrate that the proposed technique can efficiently segment video sequences with fast moving, newly appearing, or disappearing objects in the scene.