Prof. Rafeef Abugharbieh
Computational and mathematical methods for data driven processing and model-based analysis of digital images and other visual data: perception, capture; representation, modeling; enhancement, restoration; registration, fusion; feature extraction, segmentation; recognition; practical applications.
course starts with the fundamentals progressing to the state-of-the-art in
computational analysis for visual information, i.e. signals/data such as 2D
photos, 3D image volumes, video streams, graphical models etc. The topics
draw from a number of exciting fields including image processing, computer vision,
shape analysis and geometric modeling, statistical analysis and pattern recognition, image understanding
and artificial intelligence.
Problem and Project-Based Learning
Students are expected to be knowledgeable in fundamentals of signal processing and well versed in mathematical preliminaries. Coding skills in MATLAB or another suitable platform/language is essential for project work.
The course material will be presented through a combination of lectures, group readings and discussions, practice-based learning and term course project.
Students will be evaluated based on attendance, active participation,
homework assignments, reports, in class presentations and discussions of research papers,
and a (significant) term course project.