Midas: Generating mmWave Radar Data from Videos for Training Pervasive and Privacy-preserving Human Sensing Tasks

Get Started

Use the links below to download the:

• vgg16 classifier weight
• encoder-decoder weight
• real world Doppler dataset
• sample Videos

Folder description：

• doppler_data/ used to store millimeter Doppler signals,
• mmw_preprocessing/ used to store millimeter wave signal processing files,
• models/ used to store weight files,
• video_data/ used to store video files.

File description：

• train_encoder_decoder.py used to train encoder-decoder,
• train_resnet34_classifier.py used to train resnet34 classifier,
• train_vgg16_classifier.py used to train vgg16 classifier.

Dataset

Use the links below to download the:

• Real world Doppler dataset collected across 10 participants and 12 activities. Details found in paper here.
• Sample Videos for demo purposes.

Dataset directory structure：

video_data/
|----Participant_01/
|    |----angle_0/
|         |----action_01
|              |----sample_video.mp4
|         |----action_02
|              |----sample_video.mp4
|         |----...
|    |----angle_45/
|         |----...
|    |----angle_90/
|         |----...
|----...

radar_data/
|----Participant_01/
|    |----angle_0/
|         |----action_01
|              |----doppler_gt.npy
|         |----action_02
|              |----doppler_gt.npy
|         |----...
|    |----angle_45/
|         |----...
|    |----angle_90/
|         |----...
|----...

Data is divided into two parts, one is radar_data/, which contains radar data. The other part is video_data/, which contains video data, which we've only partially disclosed.

Reference

... Download paper here.

BibTex Reference:

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