TeachingWs09MotionAnalysisSeminar

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

Hauptseminar: Motion Analysis, Learning and Tracking

Nassir Navab, Diana Mateus, Loren Schwarz

Type: Advanced Seminar Course Module IN8901
Type: Master Seminar Module IN2107
Type: Seminar Module IN0014
SWS: 2+0
ECTS: 4 Credits
Time/Location: See table below
Course Language: English

Content

The seminar's participants will get a comprehensive insight into the latest developments in the domain of computer-vision-based motion analysis. The focus of this seminar is on human motion, although topics on general object motion are also available. Being able to reconstruct human poses given only limited observations, such as 2D images or wearable sensor data, is a challenging task. However, various potential fields of application, e.g. video surveillance or medical motion analysis, motivate research in this direction.

The focus of this seminar is on the following topics:

  • Acquisition of human motion data using motion capture
  • Representation of human motion in low-dimensional subspaces
  • Analysis of human motion characteristics for medical purposes
  • Machine learning approaches for human motion tracking
  • Human activity recognition techniques

The talks will be based on the latest proceedings of medical and computer science conferences, such as the International Conference on Computer Vision (ICCV), the International Conference on Computer Vision and Pattern Recognition (CVPR) and others.

Registration

Interested students, please take a look at the papers listed below and select one you would like to base your seminar talk on. Then please send an email to Loren Schwarz (), including your paper choice, your name, your birthday, program of study and Matrikelnummer. You can also propose other topics or papers related to motion analysis.

Requirements

In order to successfully complete the seminar, participants are required to (1) present the selected paper to the other participants and (2) submit a written handout. Each presentation (about 30-45min) is followed by a discussion, and everyone is encouraged to actively participate. The handout (about 10 pages) must include all references used and must be written completely in your own words and not by copy and paste. Both handout and presentation have to be done in English.

Presentation Topics

Human Motion Analysis and Tracking

  • (taken) Fossati A., Salzmann M. and Fua P.: Observable subspaces for 3D human motion recovery. Computer Vision and Pattern Recognition (CVPR), 2009
  • Huang P., Hilton A. and Starck J.: Human motion synthesis from 3D video. Computer Vision and Pattern Recognition (CVPR), 2009
  • Urtasun R. and Darrell T.: Sparse probabilistic regression for activity-independent human pose inference. Computer Vision and Pattern Recognition (CVPR), 2008
  • (taken) Ali S. and Shah M.: Floor fields for tracking in high density crowd scenes. European Conference on Computer Vision (ECCV), 2008
  • Gupta A., Chen T., Kimber D. and Davis L.: Context and observation driven latent variable models for human pose estimation. Computer Vision and Pattern Recognition (CVPR), 2008
  • Wang J., Fleet D. and Hertzmann A.: Gaussian process dynamical models for human motion. Pattern Analysis and Machine Intelligence (PAMI), 2008
  • Hou S., Galata A., Caillette F and Thacker N.: Real-time body tracking using a Gaussian process latent variable model. International Conference on Computer Vision (ICCV), 2007
  • (taken) Vlasic D., Adelsberger R., Vannucci G. and Barnwell J.: Practical motion capture in everyday surroundings. ACM Transactions on Graphics (TOG), 2007
  • Kanaujia A., Sminchisescu C. and Metaxas D.: Spectral latent variable models for perceptual inference. International Conference on Computer Vision (ICCV), 2007
  • Jenkins O., Gonzalez G and Loper M.: Dynamical motion vocabularies for kinematic tracking and activity recognition. Computer Vision and Pattern Recognition (CVPR), 2006
  • (taken) Lee C. and Elgammal A.: Human motion synthesis by motion manifold learning and motion primitive segmentation. Articulated Motion and Deformable Objects (AMDO), 2006
  • Chai J. and Hodgins J.: Performance animation from low-dimensional control signals. Computer Graphics and Interactive Techniques (SIGGRAPH), 2005

Human Activity Recognition

  • (taken) Morris B. and Trivedi M.: Learning trajectory patterns by clustering: experimental studies and comparative evaluation. Computer Vision and Pattern Recognition (CVPR), 2009
  • (taken) Tung T. and Matsuyama T.: Topology dictionary with Markov model for 3D video content-based skimming and description. Computer Vision and Pattern Recognition (CVPR), 2009
  • (taken) Weinland D., Ronfard R. and Boyer E.: Free viewpoint action recognition using motion history volumes. Computer Vision and Image Understanding (CVIU), 2006
  • Minnen D., Starner T., Essa I. and Isbell C.: Discovering characteristic actions from on-body sensor data. Symposium on Wearable Computers, 2006

Object Motion and Tracking

  • (taken) Gosch C., Fundana K., Heyden A. and Schnörr C.: View point tracking of rigid objects based on shape sub-manifolds. Computer Vision and Pattern Recognition (CVPR), 2009

Schedule

The seminar consists of an introductory meeting and four sessions. Each of the four sessions has two 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
09.11.09 16:00 Introductory Meeting: Guidelines    
18.01.10 16:15 Ali S. and Shah M.: Floor fields for tracking in high density crowd scenes. Babak Gholami Loren Schwarz
18.01.10 17:00 Morris B. and Trivedi M.: Learning trajectory patterns by clustering: experimental studies and comparative evaluation. Artashes Mkhitaryan Diana Mateus
25.01.10 16:15 Lee C. and Elgammal A.: Human motion synthesis by motion manifold learning and motion primitive segmentation. Ishan Bhattarai Loren Schwarz
25.01.10 17:00 Gosch C., Fundana K., Heyden A. and Schnörr C.: View point tracking of rigid objects based on shape sub-manifolds. Manuel de Souza Diana Mateus
01.02.10 16:15 Tung T. and Matsuyama T.: Topology dictionary with Markov model for 3D video content-based skimming and description. Elena Erastova Diana Mateus
01.02.10 17:00 Weinland D., Ronfard R. and Boyer E.: Free viewpoint action recognition using motion history volumes. Conor Haines Diana Mateus
08.02.10 16:15 Vlasic D., Adelsberger R., Vannucci G. and Barnwell J.: Practical motion capture in everyday surroundings. Denis Bakarassov Loren Schwarz
08.02.10 17:00 Fossati A., Salzmann M. and Fua P.: Observable subspaces for 3D human motion recovery. Adam Włodarkiewicz Loren Schwarz


TeachingForm
Title: Motion Analysis, Learning and Tracking
Professor: Nassir Navab
Tutors: Diana Mateus, Loren Schwarz
Type: Hauptseminar
Information: Hauptseminar, SWS: 2, ECTS: 4
Term: 2009WiSe
Abstract: The seminar's participants will get a comprehensive insight into the latest developments in the domain of computer-vision-based human motion analysis. The focus of this seminar is on the following topics: Efficient representation of human motion (human body models), learning of human motion for pose inference, human motion tracking from video images and other input data.


Edit | Attach | Refresh | Diffs | More | Revision r1.20 - 10 Nov 2009 - 15:38 - LorenSchwarz

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