Visual Computing in Winter Term 2023/2024



Course: Medieninformatik (B.Sc.)
LV-Art.: Vorlesung + Praktikum (2 + 4 SWS)
LV-Nr.: 7861
Credits: 10
Appoints.: Fr. 10:00-11:30 (seminar, D18)
Fr. 11:45-15:30 (practical work, D18)
Exam: TBA
lectureimage_3

Topics

  • Image formation and processing
  • Feature detection and matching
  • Segmentation
  • Shape from X
  • Deep Learning

Prerequisites

  • Programming (Python)
  • Calculus and linear algebra
  • Basic knowledge in computergraphics would be helpful

Documents

(for online lectures see zapp.mi.hs-rm.de, for assignment submission see read.mi.hs-rm.de

Presentations (02.02.2024)

  • Superresolution
  • Virtual Character Scanning
  • VR Painting
  • Colorization

References

  • Ma, Y.; Soatto, S.; Kosecke, J.; Sastry, S. S.; An Invitation to 3-D Vision, Springer, 2004
  • Forsyth, D.; Ponce, J.; Computer Vision. A Modern Approach, Prentice Hall, 2003
  • Hartley, R.; Zisserman, A.; Multiple View Geometry in Computer Vision, Cambridge University Press, 2003
  • Bradski, G.; Kaehler, A.; Learning OpenCV: Computer Vision with the OpenCV Library, O’Reilly Media, 2008
  • Lélis Baggio, D.; Emami, S.; Millán Escrivá, D.; Ievgen, K.; Mahmood, N.; Saragih, J.; Shilkrot, R.; Mastering OpenCV with Practical Computer Vision Projects, Packt Publishing, 2012
  • Laganiére, R.; OpenCV 2 Computer Vision Application Programming Cookbook, Packt Publishing, 2011
  • Szeliski, R.; Computer Vision: Algorithms and Applications, Springer, 2010 (http://szeliski.org/Book/)
  • Goodfellow, I., Benito, Y., Courville, A.; Deep Learning, MIT Presse, 2016 (https://www.deeplearningbook.org)