An evolving MoG for online image sequence segmentation

When segmenting image sequences, it is important to ensure the coherency of the produced segments across successive frames. In this paper, we present a method for evolving a Mixture of Gaussian (MoG) to produce such coherent segments. Using a MoG allows us to select the number of components automatically and in a principled way. The parameters of the evolving MoG can vary smoothly to track online the continuous evolution of the feature´s distribution. In addition, the complexity of the MoG can vary to cope with incoming or disappearing objects in the sequence. The method is tested on several video sequences and the results are compared to another method, which shows the advantage of the ability to change the number of components automatically for tracking changes in the scene.