199.092 Computer vision and image analysis of art
Diese Lehrveranstaltung ist in allen zugeordneten Curricula Teil der STEOP.
Diese Lehrveranstaltung ist in mindestens einem zugeordneten Curriculum Teil der STEOP.

2020W, VU, 2.0h, 3.0EC
Diese Lehrveranstaltung wird nach dem neuen Modus evaluiert. Mehr erfahren



  • Semesterwochenstunden: 2.0
  • ECTS: 3.0
  • Typ: VU Vorlesung mit Übung
  • Format der Abhaltung: Distance Learning


Nach positiver Absolvierung der Lehrveranstaltung sind Studierende in der Lage...

After successful completion of the course, students are able to...

  • explain key problems in computer image analysis of fine art
  • explain terminology and techniques used by art scholars, in particular connoisseurs
  • make use of computer methods applied to problems in analysis of fine art, based on their theoretical and practical experience gained 

Inhalt der Lehrveranstaltung

The subject of the course is the application of rigorous image processing, computer vision, pattern recognition, machine learning and artificial intelligence to problems in the history and interpretation of fine art. The lecturer of this course will be David G.Stork and the course will be held via distance learning (live video conference).

Course schedule: Nov 25, 2020 - Jan 31, 2021, Wednesday and Thursday from 6pm - 7pm (CET) via Zoom (Link provided via TUWEL)


  • Two one-hour online lectures per week (Wednesday and Thursday from 6pm - 7pm (CET))
  • One optional one-hour online "office hour" (to answer student questions, help choose programming projects, prepare for exam, etc.)
  • Email correspondence



Weitere Informationen

This is a visiting professor course of the Vienna PhD School of Informatics.

First Lecture 25.11.2020 via ZOOM (Link provided via TUWEL)

ECTS Breakdown:

  • Online lecture:  24 hr
  • Individual project, including development of code (Matlab, or language of choice):  28 hr
  • Preparation for practical assignments:  28.25 hr
  • Presentation of project to class:  .25 hr
  • Exam preparation:  30 hr
  • Final exam:  2 hr
  • Total:  112.5




  • Weekly homework exercises (verbal explanations, mathematical problems, one or two simple coding exercises):  40% of overall grad
  • Individual programming project (15-minute presentation to class plus five-page writeup with code and images):  40% of overall grade
  • Final exam:  20% of overall grade
  • Examination modalities: Two-hour "in-class" final exam


Von Bis Abmeldung bis
01.09.2020 00:00 23.10.2020 23:59


Please register in TISS.


PhD Vienna PhD School of Informatics


  • David G. Stork, Pixels & paintings:  Foundations of computer-assisted connoisseurship (Wiley) [.pdf draft manuscript distributed to students]
  • Scholarly papers from SPIE, IEEE, IS&TACM, AAAICAA (College Art Association), conferences such as CVPR, ECCVICCV, IP4AI, etc.
  • Online lectures from others (e.g., Youtube, National Gallery London, National Gallery Washington, Museum of Modern Art, ...)