Study Track: Image Analysis and Computer Vision (IACV)
The study track in Image Analysis and Computer Vision is aimed at educating specialists in the growing market for vision-based solutions to a broad range of applications. Also part of the track is physics-based modeling and simulations. The track offers a solid and broad program covering both the theoretical foundation and the state-of-the-art applications within a range of tasks. Recent developments include a significant usage of techniques from Machine Learning. Therefore, the study program includes such courses. Graduates will acquire a solid background for solving the many unsolved problems in industry, in research, within high-tech companies including those in social media, animated movies etc.
Students are expected to have a basic mathematical and statistical knowledge and an extensive knowledge and experience with programming. For the math, introductory courses within linear algebra and statistics at university level are a minimum, and more will indeed show advantageously.
If you have a bachelor in Computer Science and you enjoyed the math/stat-courses, then you probably will feel at home within the IACV-program. If you have a bachelor in math, in statistics or physics, and you have qualifications for acceptance at the MSc-CS-program, then you may fit as well.
The number of companies using IA or CV seems to explode. This partly is because a lot of new application areas are emerging and partly because the technology (and computer power) has reached a maturity allowing trusted applications. One example is within vision-based navigation of autonomous vehicles/robots. Others are within surveillance, quality inspection, analysis of sport videos, art, entertainment, human identification using face-, iris-, or fingerprint recognition etc. A huge application field deals with the analysis of the growing amount of medical scans (often in 3D), and with analysis of biological microscope images. One recent application area is related to analysis of the video data exchanged through social media. Google street view is an example of core Computer Vision.
At the moment the demand for labor with the qualifications provided by the IACV study track by far exceeds the production, and there is no sign of any decline in demand. Within research, both the industrial PhD and the ordinary PhD gives ample possibilities for further acquiring qualifications and for use of such in solving essential problems within industry and society.
Basic courses of this recommended study track
The recommended courses in the study track for Image Analysis and Computer Vision are shown below. Depending on your interest some elective or restricted elective courses may be substituted with other courses. You are strongly encouraged to contact relevant staff members for a sanity-check of your study plan.
Please notice the possibility of having two 7.5 ECTS projects (or one 15 ECTS project) in block 1 and 2 of the second year. This is highly recommended and will provide the best possible offset for the thesis work. Please make sure the paper work is done in good time before the start of a project.
|Block 1||Block 2||Block 3||Block 4|
||Advanced Programming||Advanced Computer Systems||Signal and Image Processing||Project or elective course|
|Advanced Algorithms and Data Structures||Machine Learning||Numerical Optimization||Computational Methods in Simulation|
|Year 2||Advanced Topics in Image Analysis||Project or elective course||Thesis|
|Medical Image Analysis||Project or elective course|
If you are particular interested in Machine Learning you may consider the course Advanced Topics in Machine Learning (block 1, schema C).
If you are particular interested in Computer Vision Applications you may consider the course Vision and Image Processing (block 2, schema C). If you plan to follow ATIA, then we recommend that you make a project instead of following Vision and Image Processing.
If you are particular interested in Fast implementations you may consider the Programming Massively Parallel Hardware (block 1, schema A).
If you are particular interested in Algorithmic aspects you may consider the course Randomized Algorithms (RA) (block 4, schema A).
If you are particular interested in Computer Simulations, Numerical Optimization and Animation then you may consider the courses Computational geometry (block 3, schema C).
Bachelor students may shape their bachelor study for a subsequent IACV-study track by selecting appropriate elective bachelor courses. We recommend that you strengthen your prerequisites in math by taking the courses Introduktion til Numerisk analyse (block 1, schema A). In addition we recommend Roboteksperimentarium (block 1, schema B), Introduktion til Computergrafik (blok 2, schema A) and Applied programming (block 4, schema C).