Paola La Fauci
Deep learning 3D facial reconstruction framework for prosthetic rehabilitation.
Rel. Stefano Di Carlo, Alessandro Savino. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering), 2021
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Abstract
Facial prosthetic rehabilitation aims to provide a patient affected by severe pathologies, or victim of accidents, with the restoration of their facial capability. Previous to the actual medical procedure, the process involves showing the patient what the result of rehabilitation would be. To achieve this goal, current techniques are based on the creation of wax models and other similar artifacts. However, the modern advance in computer graphic techniques as well as machine learning suggests the possibility of moving the process to a computerized domain, thus making the model derivation faster and the model itself easily editable. The ultimate goal of this thesis was to achieve an accurate 3D model of a human face that could act as a replacement to the current methods cited above and to be able to tune it according to specific parameters.
To achieve this goal different steps were followed
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