In the exercises, the relevant models are simulated on workstations, among them a face recognition system. Starting from a phenomenology of human vision, biological and psychological basics, the foundations of image processing are developed, finally leading to more advanced concepts like multi-scale and wavelet analysis, and algorithms for face and object recognition. The lecture is suited for students of computer science, biology, physics, engineering, and psychology. Digitale Bildverarbeitung, 4. Wahrnehmen - ein Lehrbuch, Kohlhammer.
Examples show the potential and limitations of the methods.
Supervised as well as unsupervised learning methods are introduced. Digitale Bildverarbeitung, 4. This approach emphasizes the evolution in time of behavioral and neural patterns as the basis of their analysis and synthesis. Dynamic stability, a concept shared with the classical biological cybernetics framework, is one cornerstone of the approach. The course will include tutorial modules the provide mathematical foundations.