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Projekt Computer Vision [ProjCV]

The goal of this master project is to build state-of-the-art software for different advanced topics in computer vision. During the project you will learn about basic image processing methods, the foundations of projective geometry, 3D cameras, super-resolution, tracking, feature detection and classification. The project is designed to be completed in two parts: In the first part, the basics of each topic will be developed in a group. All participants will create basic tools for certain computer vision applications. The following topics will be taught and implemented during the first part: - Basic image processing of grayscale and distance images - Pinhole camera and projective geometry - Stereo vision and RGB-D imaging - Super resolution - Image retrieval / Image classification In the second part each participant will implement a method which belongs to one of the aforementioned topics. We will provide data or evaluation setups which allow you to test your own implementations.

Dates & Rooms:
Monday, 16:00 - 18:00; Room: 00.153-113 CIP

This project gives you the chance to learn about current computer vision topics and get practical experience in the field during the exercises.

Last semester, the following topics were covered:

  1. Image processing of distance images
  2. Statistical Shape Models
  3. Face Recognition
  4. Super-Resolution
  5. Image Retrieval


You can register via StudONOpens external link in new window for the Computer Vision Project. During the semester lecture and exercise alternate on a weekly basis. Exercises are supervised and take place in one of the CIP pools. All exercises must be completed. For 10 ECTS credits you are required to implement a state-of-the-art/recently published algorithm selected from one of the topics above.

  • Lectures will take place in E 1.11
  • The exercises will talk place in 00.153-113, same time as above.

Please note that the first lecture on October 15th is mandatory for everyone!


You can get either 5 or 10 ECTS credits for this project. The following options are available:

5 ECTS (counts as: Hochschulpraktikum)

This option requires:

  • lectures (strongly recommended as they introduce the background required for the exercises)
  • exercises (in groups of 2 people) need to be finished on time
  • individual presentation about a state-of-the-art research paper at the end of the semester (graded if needed)


10 ECTS (counts as Hochschulpraktikum (5 ECTS) + Forschungspraktikum (5 ECTS), or Master Project Computer Science (10 ECTS))

  • lectures (strongly recommended as they introduce the background required for the exercises)
  • exercises (in groups of 2 people) need to be finished on time
  • individual coding/research project under supervision of a LME PhD student at the end of regular schedule (graded if needed)

Important: You cannot use the lecture/exercise part as a 5 ECTS research project (Forschungspraktikum). Please contact one of the PhD students at the lab if you need a research project.