@inproceedings {650,
	title = {Parametric contour estimation by simulated annealing},
	booktitle = {IEEE International Conference on Image Processing},
	year = {2003},
	address = {Spain},
	abstract = {<p>Virtually all implementations of simulated annealing are simplified by assuming discrete unknowns, however continuous-parameter annealing has many potential applications to image processing. Widely scattered problems such as formant tracking, boundary estimation and phase- unwrapping can all be approached as the annealed minimizations of continuous B-spline parameters. The benefits of simulated annealing are well known, including an insensitivity to initial conditions and the ability to solve problems with many local minima. Discrete variable annealing has seen broad application, however continuous-variable annealing is limited by the computational challenge of Gibbs sampling. In this paper we develop efficient approaches to sampling, illustrated in the context of contour tracking in noisy images.</p>
},
	keywords = {boundary estimation, continuous B-spline parameters, continuous-variable annealing, discrete variable annealing, formant tracking, Gibbs sampling, image processing, image sampling, noisy images, parametric contour estimation, phase-unwrapping, simulated annealing, splines (mathematics), tracking},
	doi = {http://dx.doi.org/10.1109/ICIP.2003.1247278},
	author = {M Jamieson and P Fieguth and L J. Lee}
}
