Project description and publications below.

Dataset and Code

We will extend this section with all raw data, models and code. For now, RNN training code, RNN input features and the ground truth poses are provided below:

• Github repository with RNN train&test code
  
• RNN features and ground truth poses (250MB, zipped)
  

You will need to install Python, Theano and CUDA.

Contact us if you have trouble running the provided code or downloading the dataset.

Patient Pose Estimation In medical collaboration with: Prof. Dr. med. Soheyl Noachtar In academic collaboration with: Dr. Marc Lazarovici Alexandru Eugen Ichim Scientific Director: Nassir Navab Contact Person(s): Felix Achilles

Keywords: Computer Vision

Abstract

In this project, we investigate machine learning algorithms for the purpose of real-time 3D human pose estimation in a hospital monitoring scenario. Patients are typically covered with a blanket and the bed is cluttered with books, laptops and other everyday objects. This makes the task more challenging than background-free human pose estimation. With the constraint of day and night monitoring capacity, we have recently published a method based on depth data which will be presented at MICCAI 2016, see link to the paper below. On this project page, you can also find the used dataset and training code. For further information, please contact Felix Achilles.

Pictures

Figure 1: Schematic of the Database Recording Method and the Deep Learning Model.

Publications

2016
	F. Achilles, A.E. Ichim, H. Coskun, F. Tombari, S. Noachtar, N. Navab PatientMocap: Human Pose Estimation under Blanket Occlusion for Hospital Monitoring Applications Proceedings of the 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Athens, Greece, October 2016 (bib)

Team

Contact Person(s)

M.Sc. Felix Achilles

Working Group

Federico Tombari

M.Sc. Felix Achilles

M.Sc. Huseyin Coskun

M.Sc. Leslie Casas

Location

Technische Universität München Institut für Informatik / I16 Boltzmannstr. 3 85748 Garching bei München Tel.: +49 89 289-17058 Fax: +49 89 289-17059

Visit our lab at Garching.

Ludwig-Maximilians-Universität München Campus Grosshadern Marchioninistrae 15 81377 München Lab - Room: 4K U1 912 Tel.: +49 89 7095 4606

Visit our lab at Klinikum Grosshadern.



internal project page

Please contact Felix Achilles for available student projects within this research project.