Computer vision is concerned with the automated analysis of still images and videos. We analyse images created by standard digital color cameras, active depth sensors (e.g. Microsoft Kinect), as well as multiple band images from astronomical telescopes.
Computer vision is rapidly becoming an essential ingredient in many daily life activities such as automatic driving assistants, face and fingerprint recognition, natural user interfaces for computers and game consoles, mobile phone applications as well as applications involving consumer digital cameras or video surveillance.
We focus on development of fundamental algorithms as well as applications of these to industrial and real-life problems, such as welding, satellite imagery, food production, saw mill industry, agriculture, human rehabilitation as well as astronomical image analysis.
Computer vision and image analysis are closely related to neighboring research areas such as machine learning, signal processing and graphics, and our research is mathematically founded combined with empirical evaluation.
Using UAV drones for mapping weeds in fields of crop (Drone)
Texture- and color-based segmentation of weeds in crop
Applications of computer vision methods such as texture analysis to astronomical data
Automatic defect detection from images of high quality furniture wood
Comparative study of interest point detectors and descriptors and development of novel algorithms
Human motion imitation (HUMIM)
Modelling, tracking and analysis of human motion, computer-assisted physiotherapeutic rehabilitation
Real-time Robots in the Meat industry
Real-time welding control2D shape modelling, image processing
- Currently we offer the following relevant courses:
- Signal and image processing
- Vision and image processing
- Advanced topics in data modelling
- CMM projects 1 and 2.
We also offer project and MSc thesis supervision in areas related to our research activities.