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.

CURRICULUM TIPO:

1° Year 

ModulesCreditsTAFSSD
12
B
ING-INF/05
12
B
INF/01
12
B
ING-INF/05
6
B
ING-INF/05
6
B
ING-INF/05
6
B
ING-INF/05

2° Year   activated in the A.Y. 2015/2016

ModulesCreditsTAFSSD
6
B
ING-INF/05
6
B
INF/01
Altre attivita' formative (taf f)
4
F
-
24
E
-
ModulesCreditsTAFSSD
12
B
ING-INF/05
12
B
INF/01
12
B
ING-INF/05
6
B
ING-INF/05
6
B
ING-INF/05
6
B
ING-INF/05
activated in the A.Y. 2015/2016
ModulesCreditsTAFSSD
6
B
ING-INF/05
6
B
INF/01
Altre attivita' formative (taf f)
4
F
-
24
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
Tre insegnamenti a scelta
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
SECS-P/10
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
FIS/01
Between the years: 1°- 2°
8
D
-

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.

A Basic activities
B Characterizing activities
C Related or complementary activities
D Activities to be chosen by the student
E Final examination
F Other training activities
S Placements in companies, public or private institutions and professional associations

Advanced recognition systems  (2015/2016)

Teaching code

4S02792

Teacher

Marco Cristani

Coordinator

Marco Cristani

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Period

I semestre dal Oct 1, 2015 al Jan 29, 2016.

Location

VERONA

Seminars 0

Learning outcomes

The course of Advanced Pattern Recognition Systems aims at providing the students with practical software instruments for solving real recognition problems, as those coming from the surveillance/quality-control/automotive/entertainment scenarios. To this sake, the lessons are organized as practical problems, which will be faced by considering theory elements coming from the Pattern Recognition course, and embedding them into MATLAB or C software. It is clear that the Laboratory sessions in this course are fundamental, and will take most of the time.

Program

PROBLEM: Detection and recognition of: people, faces, scenes and objects in general. Associated algorithms and techniques: Generative Learning, Discriminative Learning, Hybrid Learning, Boosting, GIST, SIFT (reminders of), covariances, SURF, SDALF, Bag of Words.
PROBLEM: Modeling of moving objects: tracking of single objects, groups of objects, action recognition, expression recognition. Associated algorithms and techniques: Monte Carlo Methods (Particle Filtering), Online Learning, Spline, Snakes

Examination Methods

Project or Seminar

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Teaching materials e documents