PatientPoseEstimation

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

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:
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

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)

Felix Achilles
M.Sc. Felix Achilles

Working Group

Federico Tombari
Dr. Federico Tombari
Felix Achilles
M.Sc. Felix Achilles
Huseyin Coskun
M.Sc. Huseyin Coskun
Leslie Casas
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.

Edit | Attach | Refresh | Diffs | More | Revision r1.3 - 18 Oct 2016 - 10:58 - FelixAchilles

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