In depth understanding and discussion of structural pattern recognition by means of newest literature examples

Relations between patterns in space and time; representing structure: strings, arrays, trees, graphs, maps and grammars; shape and context, embedding in an n-dimensional space; distances on a given structure; graph spectra and eccentricity; operations on structures and among structures: recognition, parsing; exact and inexact matching; modification of structure under motion and tracking; topology and homology groups (nD holes, persistence); applications. For details see http://www.prip.tuwien.ac.at/Teaching/.

lecture 15h

homework:

specify problem 15h

design and select methodology 24h

evaluation concept 5h

presentation 2h

report 14h

Written and oral

Digital Image Processing, Pattern Recognition, basic mathematical concepts: order theory, relations;

data structures: strings, arrays, trees, graphs, fromal grammars.