First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Engineering
ICT FOR INTERNET AND MULTIMEDIA
Course unit
COMPUTER VISION (Numerosita' canale 2)
INP6075837, A.A. 2017/18

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course Second cycle degree in
ICT FOR INTERNET AND MULTIMEDIA
IN2371, Degree course structure A.Y. 2017/18, A.Y. 2017/18
N2cn2
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Degree course track Common track
Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination COMPUTER VISION
Department of reference Department of Information Engineering
E-Learning website https://elearning.dei.unipd.it/course/view.php?idnumber=2017-IN2371-000ZZ-2017-INP6075837-N2CN2
Mandatory attendance No
Language of instruction English
Branch PADOVA
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge PIETRO ZANUTTIGH ING-INF/03

Mutuated
Course unit code Course unit name Teacher in charge Degree course code
INP6075837 COMPUTER VISION (Numerosita' canale 2) PIETRO ZANUTTIGH IN0521
INP6075837 COMPUTER VISION (Numerosita' canale 2) PIETRO ZANUTTIGH IN0527
INL1001836 THREE-DIMENSIONAL DATA PROCESSING (Numerosita' canale 2) PIETRO ZANUTTIGH IN0521

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses ING-INF/03 Telecommunications 9.0

Mode of delivery (when and how)
Period Second semester
Year 1st Year
Teaching method frontal

Organisation of didactics
Type of hours Credits Hours of
teaching
Hours of
Individual study
Shifts
Lecture 9.0 72 153.0 No turn

Calendar
Start of activities 26/02/2018
End of activities 01/06/2018

Examination board
Board From To Members of the board
1 A.A. 2017/2018 01/10/2017 15/03/2019 ZANUTTIGH PIETRO (Presidente)
GHIDONI STEFANO (Membro Effettivo)
CALVAGNO GIANCARLO (Supplente)
ERSEGHE TOMASO (Supplente)
MENEGATTI EMANUELE (Supplente)
MILANI SIMONE (Supplente)
TOMASIN STEFANO (Supplente)
ZANELLA ANDREA (Supplente)

Syllabus
Target skills and knowledge: The course presents the principles and techniques of computer vision. It will provide the skills required for automatic image analysis and processing and for the extraction of information from these data. Tools needed for developing real-world applications of the presented techniques will also be provided. In particular the course will present C++ applications based on the OpenCV open source library.
Examination methods: Written exam, homeworks and final project
Assessment criteria: The student will need to demonstrate that he has acquired the basic theoretical concepts of the course and that he is able to apply the theory to practical computer vision problems that can be solved using the tools discussed during the course. This will be evaluated also through the homeworks and the final project.
Course unit contents: 1. Cameras: sensors, lenses and image formation. Colors: additive and subtractive color models, color spaces, Bayer pattern.
2. Projective geometry, image formation, pinhole camera model.
3. Intrinsic and extrinsic camera calibration.
4. Image processing algorithms, low level: convolutional, bilateral and median filters. histogram processing, Fourier domain processing, morphological operators.
5. Middle level processing: edge detection, blob detection, Hough transform, segmentation: clustering-based approaches, watersheds, split and merge, region growing.
6. Image features: keypoints and descriptors.
7. High level algorithms: template matching, object recognition.
8. C++ Templates: libraries and classes, template library examples.
9. Class hierarchy and inheritance.
10. Data management for computer vision applications, applications using OpenCV.
Planned learning activities and teaching methods: Lessons and laboratories
Additional notes about suggested reading: Slides and other documents provided by the instructor
Textbooks (and optional supplementary readings)
  • Gonzalez, Rafael C.; Woods, Richard Eugene, Digital image processing. Upper Saddle River: Pearson Prentice Hall, 2010. Cerca nel catalogo
  • Szeliski, Richard, Computer visionalgorithms and applications. New York: Springer, 2011. Cerca nel catalogo
  • Klette, Reinhard, Concise Computer Vision. London: Springer, 2014. Cerca nel catalogo
  • Kaehler, Adrian, Bradski, Gary R., Learning OpenCV 3. --: O'Reilly Media, 2016. Cerca nel catalogo