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Modeling and Detection of Wrinkles in Aging Human Faces Using Marked Point Processes

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 lo-cations 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 pro-posed 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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https://hal.inria.fr/hal-01096683
Contributor : Nazre Batool <>
Submitted on : Thursday, December 18, 2014 - 1:16:31 AM
Last modification on : Friday, August 2, 2019 - 2:30:10 PM
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Nazre Batool, Rama Chellappa. Modeling and Detection of Wrinkles in Aging Human Faces Using Marked Point Processes. 12th European Conference on Computer Vision “What’s in a Face?” Workshop, Oct 2012, Florence, Italy. pp.178 - 188, ⟨10.1007/978-3-642-33868-7_18⟩. ⟨hal-01096683⟩

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