Lorenzo Lanari
Joint re-identification and damage detection in the insurance domain: training from synthetic data.
Rel. Fabrizio Lamberti, Lia Morra. Politecnico di Torino, Master of science program in Computer Engineering, 2022
Abstract
This thesis is part of a project that is concerned with the study of object re-identification and damage detection applied to images of personal belongings, in particular bikes. Object re-identification (ReID) is a computer vision based technology which aims at associating a particular object across different scenes and camera views, in order to assess whether a specific object is present in an image or video sequence regardless of the background or the object angle and position. Damage detection (DT) is the automatic process of identifying the presence of a damage on an object, and eventually assess the location and the type of the damage.
The first focus point of this thesis is the design of a computer graphics pipeline for the semi-automatic creation of synthetic data to be used for training of a Transformer-based neural network, to address the lack of training data regarding damaged bikes
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