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## MINIONS: Motion capture from INertial and visION Sensors
MINIONS is a large-scale multi-modal human motion capture dataset collected from **inertial sensors (IMUs)** and **vision sensors (RGB videos)**, designed to support research on consumer-affordable motion capture with a monocular camera and sparse IMUs, as well as broader motion understanding tasks.
### Key properties
- **Multi-modalities**: captured with up to **eight 2K RGB cameras** and **full-body IMU suits with 17 nine-axis sensors**; an **RGB-D scanner** is used to obtain textured meshes for each actor.
- **Scalability**: **5.5M+ frames** and **~440 minutes** of action sequences captured from multiple viewpoints.
- **Diversity**: **146** fine-grained action categories, including **single-person** and **multi-person interactions**.
- **Abundance of annotations**: time-synchronized labels per frame, including **2D/3D keypoints**, **joint rotations**, **SMPL parameters**, **fine-grained action labels**, and **texture**.
### Data acquisition & annotation pipeline (from the paper)
The dataset construction covers the following stages:
- **Multimedia hardware setup**: synchronized RGB cameras, full-body IMUs, and an RGB-D scanner.
- **Calibration**: camera calibration; IMU alignment to the SMPL coordinate system; camera–IMU alignment.
- **Textured mesh reconstruction**: RGB-D scanning to build textured human models and recover approximate SMPL shape parameters.
- **Global motion annotations**: tracking, 2D keypoint detection, 3D triangulation, and motion recovery by combining visual and inertial results, producing high-quality 2D/3D joints and SMPL parameters.
### Access policy (controlled access)
The dataset is **not released for indiscriminate public download**. Access is **registration-based and approval-based** for eligible users, and requires submitting information and a **signed agreement**.
- **Data License**: see `LICENSE` (full text).
- **Important**: the license grants use **solely for non-commercial, not-for-profit research and/or non-commercial educational use** (see the license for full terms).
### Citation
If you use MINIONS, please cite the corresponding paper:
- **Title**: *Motion Capture from Inertial and Vision Sensors*
```bibtex
@article{minions2026,
title = {Motion Capture from Inertial and Vision Sensors},
author = {Chen, Xiaodong and Liu, Wu and Bao, Qian and Liu, Xinchen and Dai, Ruoli and Zhang, Yongdong and Mei, Tao},
journal = {Arxiv},
year = {2026}
}
```