Abstract
Deformable models are related to other data representation methods. It was recently proposed a class of models based on a fuzzy energy function which includes many well known algorithms (snakes, elastic nets, fuzzy and hard c-means and Kohonen maps). This paper describes a probabilistic extension of these algorithms in a Bayesian framework, using Gibbs-Boltzman distributions. It is shown that the new class of models minimizes an energy function with an additional term: the log partition function. The role of the log partition function in probabilistic versions of snakes, c-means and elastic nets is studied and analytic expressions are derived in the case of probabilistic snakes. The log partition function produces an additional force field which improves the performance of these algorithms in some applications.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
