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Computer Vision Group
TUM School of Computation, Information and Technology
Technical University of Munich

Technical University of Munich

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Machine Learning for Robotics and Computer Vision

WS 2015/2016, TU München

Lecture

Location: Room 02.09.023
Date: Friday, starting at 16th October
Time: 9.15
Lecturer: PD Dr. habil. Rudolph Triebel
ECTS: 4
SWS: 3

Tutorial

Location: Room 02.09.023
Date: every second Friday, starting at 6th November
Time: 14.00
Lecturer: John Chiotellis


Contents

In this lecture, the students will be introduced into the most frequently used machine learning methods in computer vision and robotics applications. The major aim of the lecture is to obtain a broad overview of existing methods, and to understand their motivations and main ideas in the context of computer vision and pattern recognition.

Tentative Schedule:
- Introduction
- Regression
- Probabilistic Graphical Models
- Boosting
- Neural Networks and Deep Learning
- Kernel Methods
- Gaussian Processes
- Evaluation and Model Selection
- Sampling Methods
- Clustering

Lecture Slides
Homework
Exam Preparation

To prepare for the exam you can be helped by studying the questions here.

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Computer Vision Group

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85748 Garching info@vision.in.tum.de

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