DocumentCode :
3408508
Title :
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
Link To Document :
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