Title :
Motion estimation with object based regularisation
Author :
Panis, S. ; Cosmas, J.P.
Author_Institution :
Dept. of Electron. Eng., Queen Mary & Westfield Coll., London, UK
fDate :
5/9/1996 12:00:00 AM
Abstract :
A dynamic programming based matching method for motion estimation. That optimises a Bayesian maximum likelihood function in a 3-D optimisation space, is presented. The Bayesian function consists of a matching cost and an object based 2-D regularisation cost. The method gives results more accurate than block-based matching since the motion boundaries are close to the actual object boundaries
Keywords :
Bayes methods; dynamic programming; image matching; maximum likelihood estimation; motion estimation; object-oriented methods; 3D optimisation space; Bayesian maximum likelihood function; dynamic programming; matching cost; matching method; motion estimation; object based 2D regularisation cost; object based regularisation;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19960598
