TeachingSoSe2012MLCVSeminar

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

THIS WEBPAGE IS DEPRECATED - please visit our new website

Hauptseminar/Master Seminar:
Machine Learning Methods for Computer Vision Applications

Nassir Navab, Olivier Pauly, Diana Mateus, Slobodan Ilic

Type: Advanced Seminar Course Module IN8901
Type: Master Seminar Module IN2107
Type: Seminar Module IN0014
SWS: 2+0
ECTS: 4 Credits
Location: MI 03.13.010
Time See schedule below.
Course Language: English

Announcements

  • Introduction information meeting on Thursday 10th May at 11.00 in MI 03.13.010
  • The detailed schedule will be announced soon.
  • The list of topics is available.
  • All participants, please register for the seminar in TUMonline and send a mail to Olivier Pauly () including your name, your birthday, program of study and Matrikelnummer.
  • Maximum number of participants: 20

Requirements

In this Master Seminar (formerly Hauptseminar), each student is asked to select one topic from the list below. In order to successfully complete the seminar, participants have to fulfill these requirements:

  • Presentation: The selected paper is presented to the other participants (20 minutes presentation 10 minutes questions). Use the CAMP templates for PowerPoint CAMPmaster.pot, or Latex: CAMP-latex-template.zip.
  • Written Handout: A document of maximum 8 pages is written and submitted one week after the presentation. Please download and use the llncs2e.zip Latex template.
  • Attendance: Participants have to participate actively in all seminar sessions.

Each presentation is followed by a discussion and everyone is encouraged to actively participate. The handout must include all references used and must be written completely in your own words. Copy and paste wont be tolerated. Both handout and presentation have to be done in English.

Presentation Topics

Please choose one of the following papers for your seminar presentation. For obtaining the full-text PDFs, please use Google and especially Google Scholar. In case you are interested in a paper but cannot find the full text, please e-mail us.

Please send a mail to Olivier Pauly () as soon as possible with your preferred topic.

Medical Image Analysis

  • (taken) Lee, Hofmann et al.: Learning Similarity Measure for Multi-Modal 3D Image Registration, CVPR (2009)
  • Lucchi, Smith et al.a: Supervoxel-Based Segmentation of Mitochondria in EM Image Stacks with Learned Shape Features, TMI (2011)
  • (taken) Geremia, Clatz et al.: Spatial Decision Forests for MS Lesion Segmentation in Multi-Channel Magnetic Resonance, Neuroimage (2011)
  • (taken) Huh, Ker, Bise et al.: Automated Mitosis Detection of Stem Cell Populations in Phase-Contrast Microscopy Images, IEEE TMI (2011)
  • (taken) Zheng, Barbu, Georgescu et al.: Four-Chamber Heart Modeling and Automatic Segmentation for 3D Cardiac CT Volumes using Marginal Space Learning and Steerable Features, IEEE TMI (2008)
  • (taken) Montillo, Shotton et al.: Entangled Decision Forests and their Application for Semantic Segmentation of CT Images, IPMI (2011)
  • Iglesias, Konukoglu et al.: Combining Generative and Discriminative Models for Semantic Segmentation of CT Scans via Active learning, IPMI (2011)
  • (taken) Turetken, Blum et al.: Reconstructing Geometrically Consistent Tree Structures from Noisy Images, MICCAI (2010)
  • (taken) Smith, Carleton et al.: Fast Ray Features for Learning Irregular Shapes, ICCV (2009)
  • (taken) Kohlberger, Zhang et al.: Automatic Multi-Organ Segmentation Using Learning-based Segmentation and Level Set Optimization, MICCAI (2011)

Dimensionality Reduction

  • (taken) Carreira-Perpiñán and Lu: Parametric Dimensionality Reduction by Unsupervised Regression, CVPR (2010)

Image Analysis

  • (taken) Kim, Lee and Lee: Learning Full Pairwise Affinities for Spectral Segmentation, CVPR (2010)
  • (taken) Alzate and Suykens: Multiway spectral clustering with out-of-sample extensions through weighted kernel PCA, PAMI (2010)

Human Motion Analysis

  • Jiang: Human Pose Estimation Using Consistent Max-Covering, ICCV (2009)
  • (taken) Darby, Li and Costen: Tracking human pose with multiple activity models, Pattern Recognition (2010)
  • Li, Fermuller et al.: Learning Shift-Invariant Sparse Representation of Actions CVPR (2010)
  • Urtasun, Fleet, Hertzmann and Fua: Priors for People Tracking from Small Training Sets, ICCV (2005)
  • (taken) Tian, Li and Sclaroff: Articulated Pose Estimation in a Learned Smooth Space of Feasible Solutions, CVPR (2005)
  • Sigal, Black et al.: Loose-limbed People: Estimating Human Pose and Motion using Non-parametric Belief Propagation, IJCV
  • (taken) Freifeld, Weiss et al.: Contour people: A parameterized model of 2D articulated human shape, CVPR (2010)
  • (taken) Eichner, Marin-Jimenez et al.: Articulated Human Pose Estimation and Search in (Almost) Unconstrained Still Images, ETH Zurich (2010)
  • (taken) Nowozin, Rother et al.: Decision Tree Fields, ICCV (2011)
  • (taken) Girshik, Shotton et al.: Efficient Regression of General-Activity Human Poses from Depth Images, ICCV (2011)
  • (taken) Kontschieder, Rota Bulo et al.: Structured Class-Labels in Random Forests for Image Labelling, ICCV (2011)

Schedule

The seminar consists of a preliminary meeting, an introductory meeting and seminar sessions. Each of the sessions will consist of several student presentations. All seminar participants are expected to be present at every session and to actively participate in the discussion.

Date Time Topic By Supervision Material
08.02.2012 11:00-12.00 First Information Meeting Tutors   PreliminaryMeetingInfo.pdf
10.05.2012 11:00-12:00 Introduction Meeting Tutors   IntroductionMeetingInfo.pdf
19.06.2012 13:00-15:00 Parametric Dimensionality Reduction by Unsupervised Regression
Multiway spectral clustering with out-of-sample extensions through weighted kernel PCA
Sami Ghawi
Julius Adorf
Diana
Diana
 
26.06.2012 13:00-15:00 Spatial Decision Forests for MS Lesion Segmentation in Multi-Channel Magnetic Resonance
Fast Ray Features for Learning Irregular Shapes
Okan Erat
Sarthak Pati
Olivier
Vasilis
 
03.07.2012 13:00-15:00 Articulated Pose Estimation in a Learned Smooth Space of Feasible Solutions
Entangled Decision Forests and their Application for Semantic Segmentation of CT Images
Susanne Schmalkalt
Oliver Zettinig
Slobodan
Loic
 
10.07.2012 13:00-15:00 Learning Similarity Measure for Multi-Modal 3D Image Registration
Four-Chamber Heart Modeling and Automatic Segmentation for 3D Cardiac CT Volumes using MSL and Steerable Features
Decision Tree Fields
Make3d: Learning 3d scene structure from a single still image
Nicola Rieke
Rebecca Rittstieg
Florian Seidel
Michael Shelley
Olivier
Olivier
Slobodan
Slobodan
 
17.07.2012 13:00-15:00 Efficient Regression of General-Activity Human Poses from Depth Images
Contour people: A parameterized model of 2D articulated human shape
Articulated Human Pose Estimation and Search in (Almost) Unconstrained Still Images)
Anke Schwarz
Gheorghe-Alin Popescu
Fausto Milletari
Olivier
Vasilis
Vasilis
 


Literature and Helpful Links

A lot of scientific publications can be found online.

The following list may help you to find some further information on your particular topic:

Some publishers:

Libraries (online and offline):

Some further hints for working with references:

  • JabRef is a Java program for comfortable working with Bibtex literature databases. Handy feature: if you know the PubMed ID for an article, JabRef can import data from there (via "Web Search/Medline").
  • Mendeley is a cross-platform program for organising your references.

If you find useful resources that are not already listed here, please tell us, so we can add them for others. Thanks.


TeachingForm
Title: Machine Learning Methods for Computer Vision Applications
Professor: Nassir Navab
Tutors: Olivier Pauly , Slobodan Ilic , Diana Mateus , Vasileios Belagiannis , Loic Peter , Joé Lallemand (lalleman@in.tum.de)
Type: Hauptseminar
Information: Hauptseminar, SWS: 2, ECTS: 4
Term: 2012SoSe
Abstract:  


Edit | Attach | Refresh | Diffs | More | Revision r1.31 - 04 Jul 2012 - 15:26 - OlivierPauly

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif