A MODEL OF THE MRF WITH THREE OBSERVATION SOURCES FOR OBTAINING THE MASKS OF MOVING OBJECTS

The chapter describes an improved method of obtaining the masks of moving objects by means of Markov Random Field (MRF) modelling. A typical model includes only two observations: the difference in brightness between corresponding pixels in two images, and the value assigned to the pixel by the mask of temporal changes between consecutive images. In the new model, a third observation is added, that is the brightness at a pixel. Three observations are particularly useful for detecting the motion of objects with locally constant brightness. As a result, one can significantly improve the quality of the masks of moving objects, notably in the case of rotation, where there is a significant overlapping of the object on itself from one image to the other. The chapter presents equations necessary for the calculation of the energy of the MRF. The procedure called deterministic relaxation (DR) is described, which allows one to find the realization of the MRF for which the minimum of the energy of the field is achieved. Examples of obtained masks of moving objects are given.