Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
| Modules | Credits | TAF | SSD |
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Compulsory courses for Embedded & IoT SystemsCompulsory courses for Smart systems &data analytics2° Year activated in the A.Y. 2021/2022
| Modules | Credits | TAF | SSD |
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Compulsory courses for Embedded & IoT SystemsCompulsory courses for Robotics systemsCompulsory courses for Smart systems &data analytics| Modules | Credits | TAF | SSD |
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Compulsory courses for Embedded & IoT SystemsCompulsory courses for Smart systems &data analytics| Modules | Credits | TAF | SSD |
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Compulsory courses for Embedded & IoT SystemsCompulsory courses for Robotics systemsCompulsory courses for Smart systems &data analytics| Modules | Credits | TAF | SSD |
|---|
3 courses to be chosen among the followingLegend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Digital design (2021/2022)
Teaching code
4S009010
Academic staff
Coordinator
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
Period
Secondo semestre dal Mar 7, 2022 al Jun 10, 2022.
Learning outcomes
This course is aimed at providing the student with the practical and theoretical tools for virtual representation of objects and complex scene, and the analysis and modelling of three-dimensional data. Formal methods are provided for the digital processing of geometric structures, the 3D acquisition pipeline, and the analysis of rigid and non-rigid shapes. Particular emphasis will be devoted for 3D digital content creation from the observation of real scenes.
At the end of the course, this knowledge will allow the student to: implement a new system for the generation of virtual environments from the observation of real scenes, in a research context, combining formal methods for the analysis of rigid and non-rigid 3D shapes; implement different versions of 3D acquisition pipeline and analyse geometric properties of acquired shapes; deal with object deformation of non-rigid shapes.
In addition, the student must be able to identify the most appropriate 3D modelling method for a given applicative context, including the capability of extending the digital content design system to other disciplines like machine learning and robotics; the student will be independent in continuing the studies in 3D digital design from the observation of the real scenes.
The student will then be able to present the results of a digital design project, discuss with professional experts in the field, and provide the capability of adapting to the technical evolution and state of the art in the 3D digital content design.
Program
Introduction
3D data examples and representations
Differential geometry and 3D data
3D data acquisition
Registration and matching: ICP algorithm, pointwise descriptors
Analysis and computation on 3D data: normals, distances and operator
Spectral geometry processing
Mesh sampling and generation
AI and 3D data
3D Printing
Applications and conclusions
Bibliography
Examination Methods
L’esame si comporrà di due parti:
1) Valutazione Homework e progetto
2) Presentazione di articolo scientifico o orale
