Introduction to Computer Vision (English)

Termin(e)
Lecture /w Excercise

Tuesday, 11am - 1pm; Monday 1-3pm G29-K059 & G29-335

Prof. Dr.-Ing. Klaus Tönnies

There are no excercises/project appointments in the first 2 weeks. Instead, there will be 2 lectures instead of one!

Computer vision is derived from the term human vision (i.e. visual perception of the human being). Computer vision methods describe processes of visual perception algorithmically on different levels or replace them with equivalent processes, so that recorded camera images can be automatically interpreted or analyzed. Computer Vision may be differentiated into Early Vision and High Level Vision. Early Vision methods derive generic information such as depth or motion from images whereas High Level Vision focuses on the analysis of objects depicted in the images. Examples are object classification or object detection. The aim this lecture series is to present basic algorithms from Early Vision and High Level Vision, which are part of many methods for image-based analysis in industry and research.

Lecture contents:

  1. Introduction
  2. Early Vision – Noise Suppression, Scale Space and Segmentation
  3. Early Vision – Features from Images
  4. Early Vision – The reconstruction of Depth (introduction)
  5. Stereo Vision I – Epipolar Geometry
  6. Stereo Vision II – Correspondence Analysis
  7. Motion – Optical Flow and Structure from Motion
  8. High Level Vision – The detection of Objects
  9. Template Matching
  10. Variable Templates
  11. Part-Based Models
  12. Object Tracking
  13. Object Classification (Introduction)

Courses of study:

See LSF.

Enrolment:

This course is limited to 25 students only. Please duly enrol at the LSF until the 1st of April.

Credits: 5

Language: Englisch

Accompanying project:

To be allowed to take part in the examination, students have to succesfully participate in an accompanying project. Details will be discussed within the first lecture.

Lecture
27.03.2019GCV2019-1.-Introduction.pdf
27.03.2019GCV2019-2.-Early-Vision-noise-suppression-scale-space-and-segmentation.pdf
27.03.2019GCV2019-3.-Early-Vision-features-from-images.pdf
27.03.2019GCV2019-4.-Early-Vision-reconstruction-of-depth-Introduction.pdf
27.03.2019GCV2019-5.-Stereo-Vision-I.pdf
27.03.2019GCV2019-6.-Stereo-Vision-II.pdf
27.03.2019GCV2019-7.-Motion.pdf
27.03.2019GCV2019-8.-High-Level-Vision-the-detection-of-objects.pdf
27.03.2019GCV2019-9.-Template-Matching.pdf
27.03.2019GCV2019-10.-Variable-Templates.pdf
27.03.2019GCV2019-11.-Part-Based-Models.pdf
27.03.2019GCV2019-12.-Object-Tracking.pdf
27.03.2019GCV2019-13.-Object-classification-Introduction.pdf
Project
15.04.2019Introduction.pdf