Specialisation in Geometric and Visual Computing
The last decade has witnessed a remarkable emergence and maturing of technologies dealing with visual and geometric data. Many methods that were in the domain of research labs have become classical and standard industry practice. Think of Google Goggles (a web service allowing the user to take a street image with a mobile phone and get information about the depicted objects), Google Street View and Microsoft Photosynth (photo tourism service, based on computer vision algorithms for building 3D models of cities from very large sets of images), Microsoft Kinect (an add-on to Xbox console allowing gesture-based control, based on computer vision technology to scan the 3D scene in real-time and pattern recognition algorithms to analyze the gestures), and the movie Avatar (setting a new standard both in computer graphics realism, but also remarkable for the use of very sophisticated 3D vision technologies during production). These examples belong to the field of Geometric and Visual Computing, dealing with processing and analyzing visual and geometric information. Geometric and Visual Computing is a combination of computer science (discrete algorithms, data structures, software engineering) and mathematical modelling (theoretical foundations and computational methods), which are used in the domains of computer graphics, computer vision, 2D and 3D signal processing, and pattern recognition. The curriculum of the master's specialisation in Geometric and Visual Computing is based on a synergy between computer science, mathematical models and computational methods, and domain-specific curricula in computer graphics, computational geometry, computer vision, pattern recognition, and image processing.
Various aspects of geometric computing are required for jobs dealing with CAD/CAM systems, VLSI, geographic information systems, engineering, numerical simulations, special effects and graphics (e.g. movie industry), image processing and analysis, computer vision, and multidimensional data analysis. These jobs demand specialists combining a strong theoretical background in math, expertise in geometry, knowledge of computational methods, and software development skills.
Across the two years students must acquire:
- 30 ECTS out of 36 ECTS of core courses
- 18 ECTS of “Geometric and Visual Computing” tagged courses and write their thesis in the same area
6 ECTS can be acquired from non-INF Master programmes at USI.
|Computer Vision & Pattern Recognition||6||Spring|
|Graph Deep Learning||3||Spring|
|Image and Video Processing||6||Spring|