Modelling intermittently present features using nonlinear point distribution models

0Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

We present in this paper a new compact model to represent a data set based on the main idea of the Point Distribution Model (PDM). Our model overcomes PDM in two aspects, first, it is not needed all the objects to have the same number of points. This is a very important feature, since in real applications, not all the landmarks are represented in the images. And second, the model captures the nonlinearity of the data set. Some research have been presented that couples both aspects separately but no model have been presented until now that couples them as a whole. A case study shows the efficiency of our model and its improvement respect the models in the literature. © Springer-Verlag Berlin Heidelberg 2007.

Cite

CITATION STYLE

APA

Sanroma, G., & Serratosa, F. (2007). Modelling intermittently present features using nonlinear point distribution models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4872 LNCS, pp. 260–273). Springer Verlag. https://doi.org/10.1007/978-3-540-77129-6_25

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free