This repo is used for optimzation and visualization for MMVP dataset:

MMVP: A Multimodal MoCap Dataset with Vision and Pressure Sensors
He Zhang, Shenghao Ren, Haolei Yuan, Jianhui Zhao, Fan Li, Shuangpeng Sun, Zhenghao Liang, Tao Yu, Qiu Shen, Xun Cao

1. The MMVP dataset (the "Dataset") is available for non-commercial research purposes only. Any other use, in particular any use for commercial purposes, is prohibited. This includes, without limitation, incorporation in a commercial product, use in a commercial service, as training data for a commercial product, for commercial ergonomic analysis (e.g. product design, architectural design, etc.), or production of other artifacts for commercial purposes including, for example, web services, movies, television programs, mobile applications, or video games. The dataset may not be used for pornographic purposes or to generate pornographic material whether commercial or not. The Dataset may not be reproduced, modified and/or made available in any form to any third party without Tsinghua University’s prior written permission.
2. You agree not to reproduce, modified, duplicate, copy, sell, trade, resell or exploit any portion of the images and any portion of derived data in any form to any third party without Tsinghua University’s prior written permission.
3. You agree not to further copy, publish or distribute any portion of the Dataset. Except, for internal use at a single site within the same organization it is allowed to make copies of the dataset.
4. Tsinghua University reserves the right to terminate your access to the Dataset at any time.

Visualizing code has been released. Follow the step below for visualizing:

1. Fill out this form to request authorization to use MMVP for non-commercial purposes. It may take one week to get reply. Or Contact Tao Yu at ([email protected]).
2. MMVP Dataset are following this structure.
3. Users could visualize dataset with the command below:

sh demo.sh

You could change frame info in configs/visualizing.yaml.
basdir is the root where you put MMVP Dataset.
dataset is fixed as 20230422.
sub_ids could be S01...S12
seq_name represents the seq under the sub_ids you select.
Noticing that frame_idx may not cover all frames and could be selected in annotations/smpl_pose.

We provide a few frames in debug/ for visualizing. The visualizing result will be saved in output/. Here is a example for visualizing result:

MMVP dataset are following the structure below:

images
└── 20230422
    ├── S01
    ├── ...
    └── S12
        ├── MoCap_20230422_145333
        ├── ...
        └── MoCap_20230422_150723
            ├── color
            ├── depth
            ├── depth_mask
            └── calibration.npy
annotations
└── 20230422
    ├─ floor_info
    │   ├── floor_S01.npy
    │   ├── ...
    │   └── floor_S12.npy
    │
    └─ smpl_pose
        ├── S01
        ├── ...
        └── S12
            ├── MoCap_20230422_145333
            ├── ...
            └── MoCap_20230422_150723

If you find our work useful in your research, please cite our paper MMVP:

@inproceedings{Zhang2024MMVP,
    title={MMVP: A Multimodal MoCap Dataset with Vision and Pressure Sensors},
    author={He Zhang, Shenghao Ren, Haolei Yuan, Jianhui Zhao, Fan Li, Shuangpeng Sun, Zhenghao Liang, Tao Yu, Qiu Shen, Xun Cao},
    journal={CVPR},
    year={2024}
}

• Tao Yu ([email protected])