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Computer Vision Group
TUM Department of Informatics
Technical University of Munich

Technical University of Munich



Statistical Methods and Optimization in Computer Vision

WS 2012/13, TU München


Location: Room 02.09.023
Date: Thursday, starting at October 25th
Time: 11.15am
Lecturer: Dr. Claudia Nieuwenhuis
SWS: 3


Location: Room 02.09.023
Date: 6.11.2012, every other week
Time: 10.15am
Lecturer: Eno Töppe

The course will be held in English.

There will be no lecture on January 31st!


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 containing large amounts of data. 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

- optimization methods such as variational approaches, PDEs, MRFs

Slides and Exercises

The lecture slides and exercise sheets can be downloaded here.

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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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French-German Machine Learning Symposium

French-German Machine Learning Symposium

The French-German Machine Learning Symposium aims to strengthen interactions and inspire collaborations between both countries. We invited some of the leading ML researchers from France and Germany to this two-day symposium to give a glimpse into their research, and engage in discussions on the future of machine learning and how to strengthen research collaborations in ML between France and Germany.

The list of speakers includes Yann LeCun, Cordelia Schmid, Jean-Bernard Lasserre, Bernhard Schölkopf, and many more! For the full program please visit the webpage.


Ron Kimmel (Technion - Israel Institute of Technology) will give a talk in the TUM AI lecture series on May 6th, 3pm! Livestream


4Seasons Dataset: We have released a novel dataset for benchmarking multi-weather SLAM in autonomous driving.


Hao Li (Pinscreen) will give a talk in the TUM AI lecture series on April 22nd, 8pm! Livestream


Thomas Pock (TU Graz) will give a talk in the TUM AI lecture series on April 15th, 3pm! Livestream