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Courses

Winter semester 2019/20

We offer the Master level lecture Methods for human motion modeling and capturing (KIS entry).

Fridays, 11:45 - 13:15, room 48-210

Description

In this lecture you learn how to deduce biomechanically interpretable movement data from sensor measurements (in particular body-worn inertial measurement units). The focus of the lecture will be on models and methods from sensor fusion (recursive and optimization based), system identification and machine learning. The needed basics in human anatomy will also be provided. In hands-on sessions you will get the opportunity to apply the learnt methods to real data captured in our motion lab.

The lecture addresses master level students of computer science and applied mathematics.

News

Material (to be linked here)

  • Lecture 1 (Introduction)
  • Lecture 2 (Human body - kinematic models - marker-based optical motion capture)
  • Lecture 3 (3D rigid body kinematics, motion lab visit)
  • Lecture 4 (Introduction to inertial motion capturing), Exercise sheet 1 (IMU data): session on December 6, 2019, 10-11:30, room 48-231, Solution 1
  • Lecture 5 (Introduction to Bayesian filtering)
  • Lecture 6 (Kalman filter), Exercise sheet 2 (Kalman filter): session on December 20, 2019, 10-11:30, room 48-231, Solution 2
  • Lecture 7 (Extended Kalman filter)
  • Lecture 8 (Application of the EKF to IMU based human kinematics estimation), Exercise sheet 3 (EKF based kinematics estimation and pose-based IMU-to-segment calibration): session on January 17, 2020, 10-11:30, room 48-231, Solution 3
  • Lecture 9 (Probabilistic sensor fusion and parameter estimation from an optimization perspective)
  • Lecture 10 (Bayesian linear regression)
  • Lecture 11 (Gaussian process regression)
  • Lecture 12 (Probabilistic deep neural networks)
  • Lab session (Probabilistic regression and classification)

Summer semester 2019

We offer the Master level project Simulation, capturing and analysis of human motion

News

  • The final presentations will take place at 21.08.19, 10-12 am, room 48-654
  • The intermediate meeting will take place at 28.05.19, 10-12 am, room 48-654
  • Please check the information on the seminar/project organisation here.

Topics

The available topics will focus on human motion simulation / behavior imitation learning

Example references:

  • Generative Adversarial Imitation Learning (GAIL): paper, code base
  • Learning human behaviors from motion capture by adversarial imitation: paper, code base

For students, who are interested in starting a master thesis in this area (e.g. after a seminar/project):

  • InfoGAIL: Interpretable Imitation Learning from Visual Demonstration: paper, code base

The idea is to apply the presented techniques to our own motion capture databases (walking of healthy people and patients) for automatically identifying different movement patterns (physiological gait, limping), for being able to sample motion patterns (data augmentation) or for matching to known gait patterns.

All code bases use Tensorflow for the machine learning part.

If you are interested, please write an email to Gabriele Bleser latest until 12.4.2019

Winter semester 2018/19

We offer the Master level lecture Methods for human motion modeling and capturing (KIS entry).

Fridays, 11:45 - 13:15, room 48-210

Description

In this lecture you learn how to deduce biomechanically interpretable movement data from sensor measurements (in particular body-worn inertial measurement units). The focus of the lecture will be on models and methods from sensor fusion (recursive and optimization based), system identification and machine learning. The needed basics in human anatomy will also be provided. In hands-on sessions you will get the opportunity to apply the learnt methods to real data captured in our motion lab.

The lecture addresses master level students of computer science and applied mathematics.

News

  • The exam results are published in our showcase (opposite wall of room 48-453). The exam inspection will be at 18.4.2019 in room 48-490, 13:30-15:30.
  • The lab session „Probabilistic regression and classification“ (10-11:30, room 48-231) and the question lecture (11:45-13:15, room 48-210) both have to be shifted by one week to February 15, due to illness
  • The written exam will take place at 22.3.2019, 10-12:00, room 46-110, please register for the exam
  • Exam preparation:

  • The last lecture slot will be reserved for answering questions
  • Please participate to the courses survey to help us to continuously improve the lecture and exercises

Material

  • Lecture 1 (Introduction): If you have questions to the Matlab tutorial, please contact me.
  • Lecture 2 (Human body - kinematic models - marker-based optical motion capture)
  • Lecture 3 (3D rigid body kinematics)
  • Lecture 4 (Introduction to inertial motion capturing), Exercise 1 (IMU data): session on November 30, 2018, 10-11:30, room 48-231, Solution 1
  • Lecture 5 (Introduction to Bayesian filtering)
  • Lecture 6 (Kalman filter), Exercise 2 (Kalman filter): session on December 21, 2018, 10-11:30, room 48-231, Solution 2
  • Lecture 7 (Extended Kalman filter)
  • Lecture 8 (Application of the EKF to IMU based human kinematics estimation), Exercise 3 (EKF based kinematics estimation and pose-based IMU-to-segment calibration): session on January 11, 2019, 10-11:30, room 48-231, Solution 3
  • Lecture 9 (Probabilistic sensor fusion and parameter estimation from an optimization perspective)
  • Lecture 10 (Bayesian linear regression)
  • Lecture 11 (Gaussian process regression)
  • Lecture 12 (Probabilistic deep neural networks)
  • Lab session (Probabilistic regression and classification)

Summer semester 2018

We offer the Master level project Simulation, capturing and analysis of human motion (KIS entry)

A list of possible topics can be found here.

If you are interested, please write an email to Gabriele Bleser.

Winter semester 2017/18

We offer the Master level lecture Human motion modeling and capturing (KIS entry).

Fridays, 11:45 - 13:15, room 48-379

News

  • The question lecture will be at March 2, 2018, 11:45-13:15, room 48-379
  • The content of the last lecture will not be part of the exam
  • Please download the latest versions of the slides. Some slides were updated.
  • Questions for lectures 9 to 11 available
  • There will be a lab session on Gaussian process regression and classification (implementation in Python) on February 9, 10-11:30 am, room 48-231.
  • Note, the slot on January 26, 10-11:30 am was used to repeat the session for exercise 3, which most of you had missed
  • The exam period will be from March 12, 2018 to March 23, 2018 (time slots between 9-12 am, 2-4 pm). First make an appointment (email to Gabriele Bleser), then register at the examination office (examination number 67354).
  • Unfortunately, the lecture on January 12 has to be canceled! The exercise will take place! The next regular lecture will be on January 19. The current plan is to make up the missed appointment on January 26, 10-11:30, room 48-231 (additionally to the regular lecture slot). This will be discussed in the next session.

Material

Description

In this lecture you learn how to deduce biomechanically interpretable movement data from sensor measurements (in particular body-worn inertial measurement units). The focus of the lecture will be on models and methods from sensor fusion (recursive and optimization based), system identification and machine learning. The needed basics in human anatomy will also be provided. In hands-on sessions you will get the opportunity to apply the learnt methods to real captured data captured in our motion lab.

The lecture addresses master level students of computer science and applied mathematics.

Summer semester 2017

We offer a project on human body motion capture in the modeling seminar (AG Technomathematics).

Summer semester 2016

We offer the following courses: Project / seminar "Simulation, capturing and analysis of human motion".

Winter semester 2015/16

We offer the following courses: Project / seminar "Simulation, capturing and analysis of human motion"

Summer semester 2015

We offer the following courses: