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.
Academic calendar
The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
| Period | From | To |
|---|---|---|
| Primo semestre | Oct 3, 2022 | Jan 27, 2023 |
| Secondo semestre | Mar 6, 2023 | Jun 16, 2023 |
Exam calendar
Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.
Should you have any doubts or questions, please check the Enrolment FAQs
Academic staff
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 enrolment year.
| Modules | Credits | TAF | SSD |
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1° Year
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2° Year
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Legend | 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.
Computer Vision (2022/2023)
Teaching code
4S009013
Credits
6
Coordinatore
Language
English
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
The teaching is organized as follows:
Teoria
Laboratorio
Learning objectives
This course is aimed at providing the student with the practical and theoretical tools that enables the recovery of the three-dimensional structure of a scene starting from its two-dimensional projections, the images. Formal methods are provided for image acquisition and extraction of 3D information on several applicative contexts by focusing on the processing of real and noisy data. At the end of the course, the student will be able to implement a new vision system, also in a research context, through the integration of different formal methods on the 3D estimation from images and the use of different acquisition sensors. This knowledge will allow the student to: i) exploit the knowledge of computer vision on different applicative scenarios; ii) master the analysis of real and heterogeneous data; iii) address real time performances. At the end of the course, the student will be able to: i) identify the vision method most suitable to the involved applicative context, and customize the vision system involving other disciplines like machine learning; ii) continue independently his/her studies in the field of computer vision and analysis of 3D data independently.
Prerequisites and basic notions
It is useful to remind the notions of linear algebra, mathematical analysis, and numerical methods. These notions will be reviewed during the course.
Program
- Geometry of the pinhole camera
- Calibration
- Epipolar geometry
- Triangulation
- Planes and homographies
- Structure and motion from images
- Autocalibration
- Dealing with noise and outliers
- Image matching
- Non-rigid objects
- Laboratory exercise
Bibliography
Didactic methods
Lectures, blackboard exercises, laboratory exercises. Talks by professionals from the industrial sector.
Learning assessment procedures
The exam can be obtained with three different options:
A) Oral with discussion on lab exercise .
B) Project with discussion on lab exercise.
Oral is a discussion on the program. The aim is to verify the knowledge of theoretical and practical aspects of involved topics.
The discussion of lab exercise consists of the delivering of an archive with the scripts that implement the vision algorithms described in the program. The discussion aims at verifying the correct practical implementation of the theoretical aspects addressed during the course.
The project is focused on a specific and innovative topic that is identified with the teacher. The topic can be an open issue of the state of the art or a specific applicative theme. The student will be able to generalize the knowledge acquired during the course for the solution of new computer vision problems.
Evaluation criteria
The discussion of the laboratory exercises represents a barrier (positive or not negative). The oral mark is divided into the following criteria: 18-23: the student knows the basic subject. 24-27: the student links the topics well. 28-30L: the student masters the more advanced aspects. The grade of the project is divided into the following criteria: 18-23: the project is a simple extension of the exercises carried out in class. 24-27: the project involves innovative topics not addressed in the classroom. 28-30L: the project involved state-of-the-art topics.
Criteria for the composition of the final grade
Max 30L
Exam language
italian or english
Type D and Type F activities
The educational activities of type D are chosen by the student, those of type F are further knowledge useful for entering the world of work (internships, soft skills, project works, etc.). According to the Didactic Regulations of the Course, some activities can be chosen and included autonomously in the booklet, others must be approved by a special committee to verify their consistency with the study plan. Type D or F educational activities can be covered by the following activities.
1. Teachings taught at the University of Verona.
Include the teachings listed below and/or in the Course Catalogue (which can also be filtered by language of delivery via Advanced Search).
Booklet entry mode: if the teaching is included among those listed below, the student can include it autonomously during the period in which the study plan is open; otherwise, the student must submit a request to the Secretariat, sending the form to carriere.scienze@ateneo.univr.it during the period indicated.
2. CLA certificate or language equivalency.
In addition to those required by the curriculum, the following are recognized for those matriculated from A.Y. 2021/2022:
- English language: 3 CFUs are recognized for each level of proficiency above the one required by the course of study (if not already recognized in the previous course of study).
- Other languages and Italian for foreigners: 3 cfu are recognized for each proficiency level starting from A2 (if not already recognized in the previous study cycle).
These cfu will be recognized, up to a maximum of 6 cfu in total, as type F if the teaching plan allows, or as type D. Additional elective credits for language knowledge may be recognized only if consistent with the student's educational project and if adequately justified.
Those enrolled until A.Y. 2020/2021 should consult the information found here.
Booklet entry mode: request the certificate or equivalency to the CLA and send it to the Student Secretariat - Careers for career entry of the exam, via email: carriere.scienze@ateneo.univr.it
3. Soft skills
Discover the training paths promoted by the University's TALC - Teaching and learning center, intended for students regularly enrolled in the academic year of course delivery https://talc.univr.it/it/competenze-trasversali
Booklet entry mode: the teaching is not expected to be included in the curriculum. Only after obtaining the Open Badge, the CFUs in the booklet will be automatically validated. The registration of CFUs in career is not instantaneous, but there will be some technical time to wait.
4. Stage/internship period
In addition to the CFUs required by the curriculum (check carefully what is indicated on the Didactic Regulations): here information on how to activate the internship.
Teachings and other activities that can be entered autonomously in the booklet
Modules not yet included
Career prospects
Module/Programme news
News for students
There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details.
Further services
I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.
Graduation
List of theses and work experience proposals
| theses proposals | Research area |
|---|---|
| Domain Adaptation | Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Computer graphics, computer vision, multi media, computer games |
| Domain Adaptation | Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video) |
| Domain Adaptation | Computing Methodologies - IMAGE PROCESSING AND COMPUTER VISION |
| Domain Adaptation | Computing methodologies - Machine learning |
Attendance
As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.Please refer to the Crisis Unit's latest updates for the mode of teaching.
