A Markov Point Process model for wrinkles in human faces

Author

Batool, Nazre ; Chellappa, Rama

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA

fYear

2012

fDate

Sept. 30 2012-Oct. 3 2012

Firstpage

1809

Lastpage

1812

Abstract

In this paper, we present a new generative model for wrinkles on aging human faces based on Markov Point Processes (MPP) where wrinkles are considered as stochastic spatial arrangements of sequences of line segments. The model is then used in a Bayesian framework to localize the wrinkles in images. In aging human faces, wrinkles mostly appear as discontinuities in surrounding grayscale texture. The intensity gradients due to wrinkles are enhanced using filters and used as data to detect more probable locations and directions of line segments. Wrinkles are localized by sampling MPP using the Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm. Experiments on images obtained from uncontrolled acquisition conditions are presented.

Keywords

Bayes methods; Markov processes; Monte Carlo methods; face recognition; filtering theory; Bayesian framework; MPP; Markov point process model; RJMCMC; filtering theory; grayscale texture; human face aging; human face wrinkles; intensity gradients; line segment sequences; reversible jump Markov Chain Monte Carlo; stochastic spatial arrangements; Aging; Computational modeling; Humans; Image resolution; Image segmentation; Markov processes; Skin; Markov Point Process; Reversible Jump Markov Chain Monte Carlo; Wrinkles; stochastic geometrical model;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2012 19th IEEE International Conference on

Conference_Location

Orlando, FL

ISSN

1522-4880

Print_ISBN

978-1-4673-2534-9

Electronic_ISBN

1522-4880

Type

conf

DOI

10.1109/ICIP.2012.6467233

Filename

6467233