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ICIP
2001
IEEE

Multiresolution Gaussian mixture models for visual motion estimation

9 years 9 months ago
Multiresolution Gaussian mixture models for visual motion estimation
This paper introduces a new 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 and can adapt to smooth motions. After a brief presentation of the theory, it is shown how MGMM can be applied to the estimation of visual motion.
Roland Wilson, Andrew Calway
Added 25 Oct 2009
Updated 27 Oct 2009
Type Conference
Year 2001
Where ICIP
Authors Roland Wilson, Andrew Calway
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