Location:02.09.023
Time and Date: every Thursday, 3.15 pm
Lecturer: Dr. Claudia Nieuwenhuis
Start: 5th of May

Statistics is the foundation of many powerful tools in computer vision. This lecture will cover a number of widely used and important techniques for the analysis of images. We will discuss a selected number of approaches concerning their mathematical theory and implementation details. Topics will cover

• necessary basics in statistics, e.g. distributions, conditional distributions, marginal distributions, cumulative distribution functions, MAP, MLP, Bayes theorem, hypothesis tests
• subspace methods such as principal component analysis, idependent component analysis, linear discriminant analysis, e.g. with application to face recognition
• density estimation and sampling methods such as Parzen density estimation and particle filtering, e.g. with application to image segmentation and tracking
• learning and classification approaches such as Support Vector Machines, Neural Networks, Graphical Models and Dictionary Learning

The lectures will be held in English.

Location: 02.09.023
Time and Date: every Tuesday, 2.15 pm
Organization: Eno Töppe
Start: 17th of May