Paysan, Pascal. Statistical modeling of facial aging based on 3D scans. 2010, PhD Thesis, University of Basel, Faculty of Science.
Official URL: http://edoc.unibas.ch/diss/DissB_9184
Using the 3D scans we learn the correlation between physical attributes such as weight, height, and especially age and faces. With the learned correlation, we present a novel way to simultaneously manipulate different attributes and demonstrate the capability to model changes caused by aging. Using the attributes of the face model in conjunction with a skull model developed in the same research group, we present a method to reconstruct faces from skull shapes which considers physical attributes, as the body weight, age etc.
The most important aspect of facial aging that can not be simulated with the Morphable Model is the appearance of facial wrinkles. In this work we present a novel approach to synthesize age wrinkles based on statistics. Our wrinkle synthesis consists of two main parts: The learning of a generative model of wrinkle constellations, and the modeling of their visual appearance. For learning the constellations we use kernel density estimation of manually labeled wrinkles to estimate the wrinkle occurrence probability. To learn the visual appearance of wrinkles we use the fine scale skin structure captured with our improved scanning method. Our results show that the combination of the attribute fitting based aging and the wrinkle synthesis, facilitate a simulation of visually convincing progressive aging. The method is without restrictions applicable to any face that can be represented by the Morphable Model.
|Committee Members:||Weber, Andreas|
|Faculties and Departments:||05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Computergraphik Bilderkennung (Vetter)|
|Bibsysno:||Link to catalogue|
|Number of Pages:||177 S.|
|Last Modified:||30 Jun 2016 10:41|
|Deposited On:||21 Jan 2011 15:25|
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