Submission #355

Submission information
Submitted by Anonyme (not verified)
Mon, 11/12/2018 - 09:49
Marie Curie PhD: Stochastic Geometric modelling and 3D image analysis for human face prostheses
PhD Thesis
Università degli Studi di Milano
uRoboptics (Portugal)
Extracting usable parametric geometry models from point data is an open challenge. Assuming a set of point clouds obtained from instances of an (unknown) parametric class of 3D objects, the challenge is to recover, by developing suitable statistical methods on manifolds or in non Euclidean spaces, the underlying parametric surface model, knowing that point clouds are corrupted with noise, missing data, outliers and are non-uniformly sampled with different densities. Prior work, describing human lower legs, was capable of achieving the required objectives with a dataset consisting of a hundred human scans. In this 3 years project, surface models with high intrinsic curvature will be considered, requiring both different modelling techniques and the creation of much larger real-world datasets. Registration of these datasets in a common reference frame, prior to model extraction, is a common pre-processing operation, consisting of identifying shared features, which can be pre-aligned. The industrial goal for this student will be to recover models of human face features (e.g. ears, noses) for the prosthetic industry, which require high quality colour models. In this setting, model instantiation is constrained by the border conditions of the existing face shape and texture to which the generated model will need to fit. See also
48000 per year (gross salary)
Mon, 12/31/2018