MGMM: multiresolution Gaussian mixture models for computer vision

Introduces a generalisation of scale-space and pyramids, which combines statistical modelling with a spatial representation. The representation uses the familiar concept of multiple resolutions, but applied to a Gaussian mixture representation of the image-hence the title MGMM. It is shown that MGMM can approximate any probability density. Examples show how MGMM can be applied to problems such as segmentation and motion analysis