Contour Organisation with the EM Algorithm
Abstract
This paper describes how the early visual process of contour organ(cid:173) isation can be realised using the EM algorithm. The underlying computational representation is based on fine spline coverings. Ac(cid:173) cording to our EM approach the adjustment of spline parameters draws on an iterative weighted least-squares fitting process. The expectation step of our EM procedure computes the likelihood of the data using a mixture model defined over the set of spline cover(cid:173) ings. These splines are limited in their spatial extent using Gaus(cid:173) sian windowing functions. The maximisation of the likelihood leads to a set of linear equations in the spline parameters which solve the weighted least squares problem. We evaluate the technique on the localisation of road structures in aerial infra-red images.
Cite
Text
Leite and Hancock. "Contour Organisation with the EM Algorithm." Neural Information Processing Systems, 1996.Markdown
[Leite and Hancock. "Contour Organisation with the EM Algorithm." Neural Information Processing Systems, 1996.](https://mlanthology.org/neurips/1996/leite1996neurips-contour/)BibTeX
@inproceedings{leite1996neurips-contour,
title = {{Contour Organisation with the EM Algorithm}},
author = {Leite, José A. F. and Hancock, Edwin R.},
booktitle = {Neural Information Processing Systems},
year = {1996},
pages = {880-886},
url = {https://mlanthology.org/neurips/1996/leite1996neurips-contour/}
}