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
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea magistrale in Ingegneria e scienze informatiche - Enrollment from 2025/2026The 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 |
|---|
2° Year activated in the A.Y. 2017/2018
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
2 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.
Computer Vision (2016/2017)
Teaching code
4S00079
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
Period
I sem. dal Oct 3, 2016 al Jan 31, 2017.
Learning outcomes
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. The process of image acquisition will be introduced describing several 3D to 2D projection models and focusing on the relations between the involved cameras. In the context of the CdS, the course provides the knowledge for the extraction of 3D information form 2D sources that are important for the automatic recognition of image content.
At the end of the course, the student will be able to address methodological and practical aspects of different computer vision problems. The student will be able to generalize the acquired knowledge for the design, implementation and documentation of new projects on innovative applications.
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
- Laboratory exercise
| Author | Title | Publishing house | Year | ISBN | Notes |
|---|---|---|---|---|---|
| E. Trucco, A. Verri | Introductory techniques for 3D Computer Vision (Edizione 1) | Prentice-Hall | 1998 | 0132611082 | |
| R. Hartley, A. Zisserman | Multiple View Geometry in Computer Vision (Edizione 2) | Cambridge University Press | 2004 | ||
| Andrea Fusiello | Visione Computazionale | ilmiolibro.it | 2008 |
Examination Methods
The exam can be obtained with three different options:
A) Oral with discussion on lab exercise (max 28/30, average between the two modalities).
B) Project with discussion on lab exercise (max 28/30, average between the two modalities).
C) Oral+Project (average between the two modalities).
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.
