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Modeling And Detection Of Wrinkles In Aging Human Faces Using Marked Point Processes

N. Batool, R. Chellappa
Published 2012 · Computer Science

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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.
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This paper is referenced by
10.1109/ICIST.2015.7288973
Extraction and measurement of facial wrinkles
P. Zhou (2015)
Modeling and Analysis of wrinkles on aging Human Faces
Nazre Batool (2014)
10.1117/12.2182920
Robust crack detection strategies for aerial inspection
Emanuel Aldea (2015)
10.1016/j.patcog.2016.07.023
A survey on curvilinear object segmentation in multiple applications
Pedro Bibiloni (2016)
10.1016/j.patcog.2014.08.003
Fast detection of facial wrinkles based on Gabor features using image morphology and geometric constraints
Nazre Batool (2015)
10.1007/978-981-15-2475-2_48
Age Group Estimation from Human Iris
Minakshi R. Rajput (2019)
COMBINING MARKOV RANDOM FIELD AND MARKED POINT PROCESS FOR MICROSCOPY IMAGE MODELING
Huixi Zhao (2016)
10.1117/1.JEI.24.6.061119
Robust crack detection for unmanned aerial vehicles inspection in an a-contrario decision framework
Emanuel Aldea (2015)
D APPROACH TO SKIN WRINKLES SEGMENTATION
TIENNE DECENCIÈRE (2019)
10.1016/j.cviu.2016.01.009
Does "lie to me" lie to you? An evaluation of facial clues to high-stakes deception
Lin Su (2016)
10.1049/iet-bmt.2014.0053
Overview of research on facial ageing using the FG-NET ageing database
G. Panis (2016)
10.32628/IJSRST173870
Age Group Determination from Face Using Texture Classification based on Probabilistic Non-Extensive Entropy
Aruna B. Bhat (2017)
10.4236/oalib.1104541
Building Artificial Intelligence for Dermatological Practice
Brian Tian (2018)
Number 7
Ashwini Mawale (2017)
10.1109/TIP.2014.2332401
Detection and Inpainting of Facial Wrinkles Using Texture Orientation Fields and Markov Random Field Modeling
N. Batool (2014)
10.1007/978-3-319-25958-1_11
Modeling of Facial Wrinkles for Applications in Computer Vision
Nazre Batool (2016)
10.1109/SMC.2017.8122755
Automated assessment of facial wrinkling: A case study on the effect of smoking
Omaima FathElrahman Osman (2017)
10.1109/FG.2013.6553719
Assessment of facial wrinkles as a soft biometrics
N. Batool (2013)
10.1109/TCI.2016.2579601
A Hybrid Markov Random Field/Marked Point Process Model for Analysis of Materials Images
Huixi Zhao (2016)
10.1109/ICIP.2014.7025278
Marked point process model for facial wrinkle detection
Seong-Gyun Jeong (2014)
10.2991/ICMEIT-19.2019.135
Detection of Facial Wrinkle based on Improved Maximum Curvature Points in Image Profiles
Die Zhou (2019)
10.1007/978-3-319-16811-1_40
Automatic Wrinkle Detection Using Hybrid Hessian Filter
Choon-Ching Ng (2014)
10.1016/j.neucom.2016.01.101
Age progression: Current technologies and applications
Xiangbo Shu (2016)
10.1109/TMM.2016.2614429
A Novel Transient Wrinkle Detection Algorithm and Its Application for Expression Synthesis
Weicheng Xie (2017)
Efficient Automatic Detection and Removal of Facial Wrinkles
S. Priya (2015)
10.1007/978-3-319-14612-6_32
Marked Point Process Model for Curvilinear Structures Extraction
Seong-Gyun Jeong (2014)
10.1109/ICPR.2016.7900249
Crack detection based on a Marked Point Process model
Jennifer Vandoni (2016)
10.5566/IAS.1925
A 2.5d approach to skin wrinkles segmentation
Etienne Decencière (2019)
Detection and Inpainting of Facial Wrinkles
Juby Susan Mathew (2016)
Detecting Facial Wrinkles based on Gabor Filter using Geometric Constraints
Ashwini Mawale (2016)
Curvilinear structure modeling and its applications in computer vision. (Modélisation de structures curvilignes et ses applications en vision par ordinateur)
Seong-Gyun Jeong (2015)
10.5120/IJCA2016907826
Facial Wrinkles Detection Techniques and its Application
Ashwini Mawale (2016)
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