Modeling and detection of wrinkles in aging human faces using marked point processes

27Citations
Citations of this article
21Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In this paper we propose a new generative model for wrinkles on aging human faces using Marked Point Processes (MPP). Wrinkles are considered as stochastic spatial arrangements of sequences of line segments, and detected in an image by proper localization of line segments. The intensity gradients are used to detect more probable locations and a prior probability model is used to constrain properties of line segments. Wrinkles are localized by sampling MPP using the Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm. We also present an evaluation setup to measure the performance of the proposed model. We present results on a variety of images obtained from the Internet to illustrate the performance of the proposed model. © 2012 Springer-Verlag.

Cite

CITATION STYLE

APA

Batool, N., & Chellappa, R. (2012). Modeling and detection of wrinkles in aging human faces using marked point processes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7584 LNCS, pp. 178–188). Springer Verlag. https://doi.org/10.1007/978-3-642-33868-7_18

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