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            [abstract] => Contact: Jörg Stückler, Prof. Dr. Daniel Cremers

For a human, it is usually an easy task to get an idea of the 3D structure shown in an image. Due to the loss of one dimension in the projection process, the estimation of the true 3D geometry is difficult and a so called ill-posed problem, because usually infinitely many different 3D surfaces may produce the same set of images.
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            [abstract] => Contact: Jörg Stückler, Prof. Dr. Daniel Cremers

We develop computer vision methods for robot systems such as micro aerial vehicles and wheeled robots. In recent years, flying robots such as quadrocopters have gained increased interest in robotics and computer vision research. To navigate safely, these robots need the ability to localize themselves autonomously using their onboard sensors.
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            [abstract] => Contact: Jörg Stückler, Prof. Dr. Daniel Cremers

We pursue direct SLAM techniques that instead of using keypoints, directly operate on image intensities both for tracking and mapping.



Direct SLAM for Monocular and Stereo Cameras

LSD-SLAM is a direct SLAM technique for monocular and stereo cameras. The camera is tracked using direct image alignment, while geometry is estimated in the form of semi-dense depth maps, obtained by filtering over many pixelwise stereo comparisons. We then build a …
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            [abstract] => Our research group is working on a range of topics in Computer Vision, Image Processing and Pattern Recognition. Computer Vision is about interpreting images. More specifically the goal is to infer properties of the observed world from an image or a collection of images. Our work combines a range of mathematical domains including statistical inference, differential geometry, continuous (partial differential equations) and discrete (graph-theoretic) optimization techniques.
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            [abstract] => Our research group is working on a range of topics in Computer Vision, Image Processing and Pattern Recognition.
We are happy to share our data with other researchers. Please refer to the respective publication when using this data.

We provide the following datasets:
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            [abstract] => We provide the following software libraries as open-source to the scientific community. 

 This CAPTCHA Recognition framework provides a C++/Python code to recognize CAPTCHAs using Active Deep Learning approach. This method is described in our research paper: CAPTCHA Recognition with Active Deep Learning (F. Stark and C. Hazırbaş and R. Triebel and D. Cremers), In GCPR Workshop on New Challenges in Neural Computation, 2015.
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	*  Datasets
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    [title] => Mathieu Aubry
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            [abstract] => Mathieu Aubry





 My current research mainly focuses on the analysis of images and shapes. This includes both their descriptions and statistics. I am also interested in image processing, computationnal photography and pattern recognition.

 I will teach a seminar in the winter semester 2011/2012 on images and shapes descriptors, beginning in November. Please visit the webpage for more details.
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            [abstract] => Multi-Sensor Fusion, SLAM, System Calibration, 3D Reconstruction

Daniel Bender studied Computer Science at Bonn University. He received his “Vordiplom” degree in 2006 and his “Diplom” degree in 2009. Since 2009 he is a research scientist at the Fraunhofer FKIE in the department Sensor Data and Information Fusion. In addition he is a Ph.D. student in the Research Group for Computer Vision, Image Processing and Pattern Recognition, Technical University of Munich headed by Professor Daniel Cremers…
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public lecture in German on Recent Developments in Computer Vision.

Research Interests

Computer vision & mathematical image analysis (segmentation, motion estimation, multiview reconstruction, visual SLAM), autonomous quadrocopters, statistical shape analysis, variational methods and partial differential equations, convex and combinatorial optimization, machine learning & statist…
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Brief Bio

Since November 2012 Julia Diebold is a PhD Student in the Research Group for Computer Vision and Pattern Recognition at the Technical University of Munich, headed by Professor Daniel Cremers.
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            [abstract] => Jakob Engel received his Bachelor degree in Computer Science in 2009 and his Master degree in December 2011 at the Technical University of Munich (Germany). He received the SIEMENS Award for the best Master's Thesis 2012 for his work on Autonomous Camera-Based Navigation of a Quadrocopter.
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            [abstract] => Interested in a Master's thesis on deep learning with convolutional neural networks? Hit me up!

About

I'm a second-year PhD student in computer science at TUM, doing research in computer vision and machine learning advised by Prof. Daniel Cremers. My current projects focus on the application of convolutional neural networks (CNNs) on tasks like optical anomaly detection and scene recognition. Research interests include: computer vision, machine learning, deep learning, convolutional networks, …
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Wanna know more about deep learning? Here is a short intro to the topic:



Google Scholar : h-index: 2, citations: 25

I recommend all students who consider doing a phd to read the PhD Grind book.
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            [abstract] => dense visual odometry, autonomous quadrocopters, large-scale 3D reconstruction, motion segmentation
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            [abstract] => Computer Vision, Motion Capturing, Image Segmentation, 3D Reconstruction, Optimization Problems, Variational Methods, Machine Learning, Robotics, Mathematics.

Maria Klodt received her “Vordiplom” degree in Computer Science in 2005 and her “Diplom” degree in Computer Science in 2007 at the University of Bonn. In her diploma thesis, she studied continuous global optimization techniques for Image Segmentation and Multiview 3D Reconstruction. From June 2005 to August 2007 she worked in the Robotics…
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Research Interests

multiview 3D reconstruction, continuous optimization, statistical approaches, GPU programming

Brief Bio

Kalin Kolev received his “Vordiplom” in Computer Science in 2002 and his “Diplom” degree in 2005 at the University of Bonn (Germany). Since January 2006 he has been a Ph.D. student in the Research Group for Computer Vision, Image Processing and Pattern Recognition headed by Professor Daniel Cremers, currently a…
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RGB-D based 3D Reconstruction, SLAM, Visual Odometry, Bundle Adjustment techniques, GPU Programming

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Robert Maier received his Bachelor's degree (2010) and his Master's degree (2013, with distinction) in Computer Science from the Technical University of Munich (Germany). 
He studied at UPC Barcelona (Spain) in 2011, before he worked as a Computer Vision Research Intern for RGB-D based 3D reconstruction at Siemens Corporate Research in Princeton, NJ (USA) in 2012.
F…
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            [abstract] => I am currently working as a postdoctoral researcher at UC Berkeley, USA. Here is my homepage.

I received my master's degree in computer science from the Technical University of Ilmenau in 2006 and a master's degree in mathematics from the University of Hagen in 2008. In 2009 I obtained a PhD degree in computer science from the University of Heidelberg. Between 2003 and 2006 I worked as an intern at Siemens Corporate Research in Princeton, NJ, USA and at the Fraunhofer Center for Advanced Media …
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            [abstract] => This is my old web page. In September 2014, I have moved to the Computer Vision and Geometry Group at ETH Zurich.
My new web page can be found here.

A list of my publications is available here.

Martin R. Oswald received his “Vordiplom” degree (2003) and a “Diplom” degree (2007) in Computer Science from Dresden University of Technology. In 2005 he studied Machine Learning and Computer Vision at the University of Technology, Sydney. From 2005 to 2007 he worked at the Institute for Civil Engineer…
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I am a member of the Computer Vision lab at TUM since August 2013, funded by an Alexander von Humboldt Postdoctoral Research Fellowship starting February 2014. In 2012 I was a JSPS Research Fellow at The University of Tokyo, Intelligent Systems and Informatics Lab. I graduated in Computer System Engineering at the University of Rome “Tor Vergata” in 2008, where I also receive…
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            [abstract] => Multi-Object Tracking, Multi-Sensor Fusion, Variational Methods, Information Fusion, Statistics,  Machine Learning.

Since 2013 Marek Schikora has the honor to lead a young and succesfull team within the Fraunhofer FKIE. Their work is focused around the topic Aerial Vision. We are part of the Sensor Data and Information Fusion research group (SDF), headed by Dr. Wolfgang Koch. Before he was working as student research assistant in the Computer Vision Group, headed by Prof. Dr. Daniel Cremers at …
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Ulrich Schlickewei studied Mathematics and Physics at the University of Freiburg i. Brsg., at the University of Rome “La Sapienza” and at the University of Paris VI. Following his Master's degree in Pure Mathematics from Paris University, Ulrich was a doctoral student at the Department of Mathematics of the University of Bonn under supervision of Prof. Dr. Daniel Huybrechts. In 2009 he received a Ph.D. for a thesis in the field of Complex Algebraic Geometry.
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Brief Bio

Frank Steinbrücker received his Bachelor's degree in 2007 and his Master's degree in Computer Science in 2008 at Saarland University (Germany).
Since September 2008 he is a Ph.D. student in the Research Group for Computer Vision,
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            [abstract] => With the support of the Technische Universität München - Institute for Advanced Study, funded by the German Excellence Initiative.





Jan Stühmer received his Diploma degree (with distinction) in Computer Science from Dresden University of Technology in 2010. In his diploma thesis he developed a novel method that allows dense 3D reconstructions with a handheld camera. In 2014/2015 he stayed as a research intern with Microsoft Research Cambridge and in 2013 as a visiting student researcher at t…
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            [abstract] => I am fascinated by the immense progress and application potential of computer vision and robotics research. My motivation is to push the state-of-the-art by developing novel approaches and applying these methods to solve real-world problems. For example, our approach to autonomous quadrocopter flight enables a low-cost quadrocopter to follow its trajectory using a camera as its main sensor while taking a series of images. Our 3D reconstruction algorithm allows to scan persons in 3D and print the…
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            [abstract] => Variational Methods, Continuous and Discrete Optimization, Computer Graphics, Mathematics, Statistical Methods

Eno Töppe studied Computer Science at Bonn University. He received the “Vordiplom” degree in 2006 and the “Diplom” degree in 2008. His master thesis was awarded the price for the best master thesis of the year by the Bonn Society for Computer Science.

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            [abstract] => Matthias has joined the Research Group for Computer Vision and Pattern Recognition as a Ph.D. student in June 2013.

In spring 2015 he spent three month at the group of Prof. Alexander Bronstein at Tel Aviv University.

Matthias received his diploma in Mathematics from Technische Universität München in 2013.
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            [abstract] => NamePositionPhoneProf. Dr. Daniel Cremers	Head of Group +49-89-289-17755Dr. Csaba Domokos	Postdoctoral Researcher	+49-89-289-17750Dr. Laura Leal-Taixe			Postdoctoral Researcher	+49-89-289-17759Dr. Michael Möller			Postdoctoral Researcher	+49-89-289-17777Dr. Frank Schmidt			Postdoctoral Researcher	        +49-89-289-17752PD Dr. habil. Rudolph Triebel		Postdoctoral Researcher+49-89-289-17792Dr. Xiaoqin Zhang		Postdoctoral Researcher+49-89-289-17753Jakob Engel			PhD Student	+49-89-289-17781Thomas F…
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 Lecture (3 h) and Exercise (3 h)
	*  Statistical Methods and Learning in Computer Vision
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	*  Practical Course: GPU Programming in Computer Vision
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            [abstract] => Inquiries for Bachelor and Master projects are always welcome. / Anfragen zu Bachelor-/Masterarbeiten und -projekten sind jederzeit herzlich willkommen!

Summer Semester 2012

	*  Practical Course: GPU Programming in Computer Vision
 (6h / 10 ECTS) block seminar during the semester break
	*  Mathematical Image Processing Seminar
(2 h / 3 ECTS)
	*  Visual Navigation for Flying Robots
Lecture (2 h / 6 ECTS) and Exercise (2 h every two weeks)
        )

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    [title] => Summer Semester 2013
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            [abstract] => Inquiries for Bachelor and Master projects are always welcome. / Anfragen zu Bachelor-/Masterarbeiten und -projekten sind jederzeit herzlich willkommen!

Summer Semester 2013

	*  Machine Learning for Robotics and Computer Vision
 Lecture (4 ECTS)
	*  Multiple View Geometry
 Lecture (3 h) and Exercise (3 h)  (8 ECTS)
	*  Visual Navigation for Flying Robots
Lecture (2 h / 6 ECTS), Exercise (2 h every two weeks), and Lab Course (4h every two weeks)
	*  Practical Course: GPU Programming in Computer…
        )

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            [bergbaue] => Julia Bergbauer
            [strekalo] => Evgeny Strekalovskiy
            [rodola] => Dr. Emanuele Rodola
            [sturmju] => Juergen Sturm
            [stueckle] => Joerg Stueckler
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    [title] => Summer Semester 2014
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            [abstract] => Inquiries for Bachelor and Master projects are always welcome. / Anfragen zu Bachelor-/Masterarbeiten und -projekten sind jederzeit herzlich willkommen!

Summer Semester 2014

	*  Practical Course: GPU Programming in Computer Vision (6h / 10 ECTS)
	*  Analysis of Three-Dimensional Shapes
Lecture (2 h) and Exercise (1 h)
	*  Multiple View Geometry
Lecture (3 h) and Exercise (3 h)
	*  Seminar: Recent Advances in the Analysis of 3D Shapes  (2 h / 4 ECTS)
	*  Autonomous Navigation for Flying Robots …
        )

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            [hazirbas] => Caner Hazirbas
            [stueckle] => Jörg Stückler
            [vestner] => Matthias Vestner
            [moellenh] => Thomas Möllenhoff
            [moellerm] => Dr. Michael Möller
            [dieboldj] => Julia Diebold
            [sturmju] => Juergen Sturm
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    [title] => Summer Semester 2015
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            [abstract] => Inquiries for Bachelor and Master projects are always welcome. / Anfragen zu Bachelor-/Masterarbeiten und -projekten sind jederzeit herzlich willkommen!

Lectures

	*  Analysis of Three-Dimensional Shapes
(4 h + 2h / 8 ECTS)
	*  Nonlinear Multiscale Methods for Image and Signal Analysis
(2 h / 4 ECTS)
	*  Multiple View Geometry
Lecture (4 h) and Exercise (2 h)
	*  Autonomous Navigation for Flying Robots (EdX MOOC course)
Lecture videos and Interactive exercises (2 ECTS)
        )

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    [creator] => Zorah Laehner
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            [laehner] => Zorah Laehner
            [moellerm] => Dr. Michael Möller
            [domokos] => Csaba Domokos
            [schmifra] => Frank Ruediger Schmidt
            [hazirbas] => Caner Hazirbas
            [triebel] => Rudolph Triebel
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    [title] => Summer Semester 2016
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            [abstract] => Inquiries for Bachelor and Master projects are always welcome.

Anfragen zu Bachelor-/Masterarbeiten und -projekten sind jederzeit herzlich willkommen!

Summer Semester 2016

Lectures

	*  Computer Vision II: Multiple View Geometry
Lecture (4 h) and Exercise (2 h)
	*  Analysis of Three-Dimensional Shapes
(4h + 2h / 8 ECTS)
	*  Convex Optimization for Computer Vision
(4h + 2h / 8 ECTS)
	*  Probabilistic Graphical Models in Computer Vision
(2h + 2h / 5 ECTS)
	*  Machine Learning for Computer Visio…
        )

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            [schlicku] => Dr. Ulrich Schlickewei
            [cremers] => Prof. Dr. Daniel Cremers
            [oswaldm] => Martin Oswald
            [aubry] => Mathieu Aubry
            [sturmju] => Juergen Sturm
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    [title] => Winter Semester 2011/12
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            [abstract] => Inquiries for Bachelor and Master projects are always welcome. / Anfragen zu Bachelor-/Masterarbeiten und -projekten sind jederzeit herzlich willkommen!

Winter Semester 2011/12

	*  Variational Methods for Computer Vision
 Lecture (3 h) and Exercise (3 h) (8 ECTS)
	*  Combinatorial Optimization in Computer Vision
 Lecture (2 h) and Exercise (2 h every two weeks) (4 ECTS)
	*  Practical Course: GPU Programming in Computer Vision
 (6h / 10 ECTS) block seminar during the semester break
	*  Seminar:…
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            [oswaldm] => Martin Oswald
            [cremers] => Prof. Dr. Daniel Cremers
            [souiai] => Mohamed Souiai
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    [title] => Winter Semester 2012/13
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            [abstract] => Inquiries for Bachelor and Master projects are always welcome. / Anfragen zu Bachelor-/Masterarbeiten und -projekten sind jederzeit herzlich willkommen!

Winter Semester 2012/13

	*  Einführung in die Informatik 1 für Ingenieure (MSE)
 Vorlesung (2 SWS) und Übung (3 SWS)
	*  Statistical Methods and Learning in Computer Vision
 Lecture (2 h) and Exercise (2 h every two weeks)
	*  Practical Course: GPU Programming in Computer Vision
 (6h / 10 ECTS) block seminar during the semester break
	*  Semin…
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    [contributor] => Array
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            [souiai] => Mohamed Souiai
            [triebel] => Rudolph Triebel
            [strekalo] => Evgeny Strekalovskiy
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    [title] => Winter Semester 2013/14
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            [abstract] => Inquiries for Bachelor and Master projects are always welcome. / Anfragen zu Bachelor-/Masterarbeiten und -projekten sind jederzeit herzlich willkommen!

Winter Semester 2013/14

	*  Variational Methods for Computer Vision
 Lecture (3 h) and Exercise (3 h) (8 ECTS)
	*  Lecture: Machine Learning for Computer Vision 
Lecture (2 h) and Exercise (1h) 
	*  Seminar: Current Trends in Machine Learning (IN 2107)
(2 h / 4 ECTS)
	*  Practical Course: GPU Programming in Computer Vision
(6h / 10 ECTS)
        )

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            [triebel] => Rudolph Triebel
            [hazirbas] => Caner Hazirbas
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    [title] => Winter Semester 2014/15
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            [abstract] => Inquiries for Bachelor and Master projects are always welcome. / Anfragen zu Bachelor-/Masterarbeiten und -projekten sind jederzeit herzlich willkommen!

Winter Semester 2014/15

	*  Variational Methods for Computer Vision
 Lecture (3 h) and Exercise (3 h) (8 ECTS)
	*   Numerisches Programmieren (in German)
Lecture (2 h) and Exercise (3 h) (6 ECTS)
	*  Seminar: Current Trends in Machine Learning (IN 2107)
(2 h / 4 ECTS)
	*  Seminar: Selected Topics in Variational Image Processing (IN 2107)
(2 h …
        )

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            [maierr] => Robert Maier
            [stueckle] => Jörg Stückler
            [souiai] => Mohamed Souiai
            [triebel] => Rudolph Triebel
            [cremers] => Prof. Dr. Daniel Cremers
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    [title] => Winter Semester 2015/16
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            [abstract] => Inquiries for Bachelor and Master projects are always welcome.

Anfragen zu Bachelor-/Masterarbeiten und -projekten sind jederzeit herzlich willkommen!

Winter Semester 2015/16

Lectures

	*  Computer Vision I: Variational Methods
 Lecture (4 h) and Exercise (2 h) (8 ECTS)
        )

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            [souiai] => Mohamed Souiai
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            [abstract] => IPAM Workshop on Convex Relaxation Methods 

February 11 - 15, 2013
University of California at Los Angeles Organizers: 
Xavier Bresson 
Antonin Chambolle 
Tony Chan 
Daniel Cremers 
Stanley Osher 
Thomas Pock 
Gabriele SteidlSymposium on Total Variation 

Monday, February 6, 2012 - 09:00-12:00
Room: FMI 02.09.023
TU München, MI-Building (Campus Garching) Speakers: 
Vicent Caselles 
Antonin Chambolle 
Daniel Cremers 
Massimo Fornasier 
Matteo Novaga 
Thomas PockWorkshop 
RGB-D Workshop on 3D Per…
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            [abstract] => ICCV 2011Variational Methods for Computer VisionOrganizers: 
Daniel Cremers 
 Bastian Goldlücke 
Thomas PockDAGM 2011Convex Optimization for Computer VisionOrganizers: 
Daniel Cremers 
 Thomas PockECCV 2010Variational Methods in Computer VisionOrganizers: 
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            [abstract] => Job Application Form

Please use this web form to submit applications.

Postdoctoral Researcher

Requirements are a strong background in mathematics and a track record in Computer Vision or related areas.

Please send application as pdf (including CV, publication list and transcripts) through this web form.
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Persönlicher Status und Werkzeuge

Home Teaching Summer Semester 2013 Visual Navigation for Flying Robots

Visual Navigation for Flying Robots

In recent years, flying robots such as autonomous quadrocopters have gained increased interest in robotics and computer vision research. For navigating safely, these robots need the ability to localize themselves autonomously using their onboard sensors. Potential applications of such systems include the automatic 3D reconstruction of buildings, inspection and simple maintenance tasks, surveillance of public places as well as in search and rescue systems.

ECTS credits: 6

This course has been distinguished with the Teach Inf Award 2012/13 at our faculty for the best lecture in computer science in the summer term 2013. Thank you very much for your support!

Content

In recent years, flying robots such as autonomous quadrocopters have gained increased interest in robotics and computer vision research. For navigating safely, these robots need the ability to localize themselves autonomously using their onboard sensors. Potential applications of such systems include the automatic 3D reconstruction of buildings, inspection and simple maintenance tasks, surveillance of public places as well as in search and rescue systems.

In this course, we will provide an overview of current techniques for 3D localization, mapping and navigation that are suitable for quadrocopters. This course will cover the following topics:

- necessary background on robot hardware, sensors, 3D transformations

- motion estimation from images (including interest point detection, feature descriptors, robust estimation, visual odometry, iteratively closest point)

- filtering techniques and data fusion

- non-linear minimization, bundle adjustment, place recognition, 3D reconstruction

- autonomous navigation, path planning, exploration of unknown environments

The lecture will be accompanied by a lab course where the students will implement their own visual navigation system. This course is an excellent preparation for a master thesis project in this area.

Lab Course

Exercise sheets will be passed out every other week, containing both theoretical problems and programming exercises (typically in C++). In an exercise group every other week, we will discuss the solutions to the theory problems and the programming problems. Active participation in the exercises is a requirement for participation in the final exam. This will be written or oral, depending on the number of attendees. The questions will cover all material presented in class. During the semester, we offer a weekly lab course where students can get programming support for the quadrocopters for the exercises.

The practical exercises will be implemented directly on a Parrot Ardrone quadrocopter, so we expect a lot of fun (and broken propellers).

Organization

The lecture will be given by Jürgen Sturm.

Lecture: Tuesday, 10:15-11:45, room 02.09.23 (FMI, Boltzmannstrasse 3)

Teaching assistants: Jakob Engel, Christian Kerl

Contact: visnav2013@vision.in.tum.de use this mail address for all questions related to the lecture and the lab course

Lab course/practice: Thursday: 14:00-15:30, room 02.05.014 (FMI, Boltzmannstrasse 3)

Registration: via TUM campus

Note that the number of participants is limited to 30. Registration in TUMonline for this course starts on 28.03.13,12:00.

Schedule

Lectures

The lectures will take place every Tuesday at 10:15 (CT), in the CVPR seminar room (02.09.023). A printer-friendly version of the lecture slides is available here.

Date Slides
16.04.2013 Introduction pdf video
23.04.2013 Linear algebra, geometry, sensors pdf video
30.04.2013 State estimation pdf video
07.05.2013 Robot control pdf video
28.05.2013 Visual motion estimation pdf video
04.06.2013 Structure from Motion pdf video
11.06.2013 RANSAC, ICP, and SLAM pdf video
18.06.2013 Dense reconstruction pdf video
25.06.2013 Guest talks (Jakob Engel, Christian Kerl, Frank Steinbrücker/TUM) pdf 1 pdf 2pdf 3 video
02.07.2013 Path planning and navigation pdf video
09.07.2013 Guest talks (Friedrich Fraundorfer/ETH and Korbinian Schmid/DLR) pdf 1video 1 pdf 2video 2
16.07.2013 Exploration, coverage and benchmarking pdf video

Lecture Videos

Lab Course

The lab courses (mandatory!) will take place every Thursday at 14:00 (sharp), in 02.05.014

Source code for the exercises

Date Topic Material
18.04.2013 Introduction to ROS Slides Exercise Sheet 0 (ROS Intro)
25.04.2013 Exercise 1: Robot Odometry Exercise Sheet 1 flight_square.bag flight_z.bag flight_manual.bag
02.05.2013 Lab 1 Solution Sheet 1
09.05.2013 no Lab (holiday)
16.05.2013 Exercise 2: Robot Localization Exercise Sheet 2 (updated 13.5.) Bagfile
23.05.2013 Lab 2 Solution Sheet 2
06.06.2013 Exercise 3 Exercise Sheet 3 control_flight.bag
13.06.2013 Lab 3 Solution Sheet 3
20.06.2013 Project: Proposal Exercise Sheet 4 (deadline updated 13.06., 2:50 p.m. )
27.06.2013 Project Lab 1
04.07.2013 Project: Mid-term Exercise Sheet 5
11.07.2013 Project Lab 2
18.07.2013 Project: Final presentation Exercise Sheet 6

Projects

Team Title Proposal Midterm Final
1 Waving recognition
2 Quadcopter Navigation through Obstacles using Potential Field
3 POI Localization and Mapping
4 Avoiding obstacles while following a line video
5 Where am I? Appearance Based Mapping
6 Simple Hand-Gesture Based Control of Quadcopters
7 Free navigation of the quadrocopter via visual waypoints
8 gofi - the golfball finder
9 Group Photo

Additional Material

Last edited 01.07.2014 15:30 by sturmju