mmRadPose

Welcome to the official repository for our mmRadPose datatset.

A detailed explanation of the dataset is provided in the corresponding publication.

If you use our dataset, please cite the following paper:

"Advanced Millimeter Wave Radar-Based Human Pose Estimation Enabled by a Deep Learning Neural Network Trained With Optical Motion Capture Ground Truth Data"

LUKAS ENGEL, JONAS MUELLER , EDUARDO JAVIER FERIA RENDON, EVA DORSCHKY, DANIEL KRAUSS, INGRID ULLMANN, BJOERN M. ESKOFIER, AND MARTIN VOSSIEK 

published in IEEE Journal of Microwaves (https://ieeexplore.ieee.org/document/10904474).

L. Engel et al., "Advanced Millimeter Wave Radar-Based Human Pose Estimation Enabled by a Deep Learning Neural Network Trained With Optical Motion Capture Ground Truth Data," in IEEE Journal of Microwaves, doi: 10.1109/JMW.2025.3535525. keywords: {Radar;Pose estimation;Deep learning;Skeleton;Laser radar;Sensors;Radar measurements;Motion capture;Cameras;Synchronization;Human pose estimation;radar;optical motion capture;millimeter wave;target list;point cloud;machine learning;deep learning},

Datasets:

POINTCLOUDS 

The pointcloud dataset contains radar pointclouds processed from raw radar data and skeleton ground truth data.

mmRadPose_pointclouds/├── p1/                  │   ├── angle0/ # angles    │   │   ├── 0 # activities│   │   │    ├── 0 # recordings│   │   │    │    ├── skeleton.npy│   │   │    │    ├── targetlist_64.npy│   │   │    ├── 1 │   │   ├── 1│   │   ├── 2│   │   ├── ... │   │   ├── 10│   │   ├── 11│   ├── angle1/│   ├── angle2/├── p2                   ├── ... ├── p12 

RAW RADAR DATA

The raw radar data dataset contains  parsed () and cutted radar and skeleton ground truth (obained via OMC) data.

radar folder:    Contains the radar data in numpy compressed archive file format (e.g. data_cube_parsed_p1_an0_ac0_r0.npz)

skeletons folder:    Contains the skeleton GT data in numpy array file format (e.g. skeleton_p1_an0_ac0_r0.npy)

File relation:    All files have an unique ID (e.g. p1_an0_ac0_r0) to identify related radar and skeleton recordings.        ID meaning:        p X = participant X        an X = angle X        ac X = action X        r X = recording X