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Instructors: Prof. Ph. D. Stefan Roth
Event type:
Integrated Course
Org-unit: Dept. 20 - Computer Science
Displayed in timetable as:
Computer Vision
Subject:
Crediting for:
Hours per week:
4
Language of instruction:
Englisch
Min. | Max. participants:
- | -
Course Contents:
- Basics of image formation
- Linear and (simple) nonlinear image filtering
- Foundations of multi-view geometry
- Camera calibration and pose estimation
- Foundations of 3D reconstruction
- Foundations of motion estimation from video
- Template and subspace methods for object recognition
- Object classification
- Object detection
- Deep networks in computer vision
Literature:
- R. Szeliski, "Computer Vision: Algorithms and Applications", Springer 2011
- D. Forsyth, J. Ponce, "Computer Vision -- A Modern Approach", Prentice Hall, 2002
Preconditions:
Having previously attended Visual Computing (20-00-0014-iv, formerly: Kanonik Human Computer Systems) ist recommended.
Further Grading Information:
After successfully attending the course, students are familiar with the basics of computer vision. They understand fundamental techniques for the analysis of images and videos, can name their assumptions and mathematical formulations, as well as describe the resulting algorithms. They are able to implement these techniques in order to solve basic image analysis tasks on realistic imagery.
Additional Information:
http://www.visinf.tu-darmstadt.de/vi_teaching/vi_lectures/index.en.jsp
Online Offerings:
moodle
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