Advanced Topics in Image Understanding

Lecture

to Project
Lecturer: Klaus Tönnies
Room: G29-K58
Time: Montag 11-13 Uhr
Pattern recognition in image analysis may be characterised as information labeling or information mapping. Pattern recognition techniques in image analysis are used for assigning a meaning to structures whose observed patterns are visible in images. The course covers statistical, syntactic and neural pattern recognition approaches.
Disciplines of study:
WPF CMA;M 2-4
WPF CV;M 1-2
WPF CV;i ab 8
WPF DKE;M 1-3
WPF IF;i ab 8
WPF IF;M 1-2
WPF INGIF;i ab 8
WPF IngINF;M 1-2
WPF WIF;i ab 8
Credits: 6
Language: deutsch/englisch

Script

1 - Introduction (Date modified: 04.04.2013)
2 - Edges, Corners, Superpixels and Blobs (Date modified: 17.04.2013)
3 - SIFT, SURF, MSER (Date modified: 04.04.2013)
4 - Texture and Shape (Date modified: 04.04.2013)
5 - Feature Reduction (Date modified: 04.04.2013)
6 - Bag of Visual Words (Date modified: 04.04.2013)
7 - Clustering (Date modified: 04.04.2013)
8 - Bayesian Decision Making I (Date modified: 04.04.2013)
9 - Bayesian Decision Making II (Date modified: 04.04.2013)
10 - Multilayer Perceptrons (Date modified: 04.04.2013)
11 - Support Vector Machines (Date modified: 04.04.2013)

Project

to the Lecture
Instructor: Klaus Tönnies
Room and time: Mi 9-11, G29-K059

Topic

Image Classification (see PDF below)

Downloads

1 - Image Classification 2013 (Date modified: 04.04.2013)