README.md

metadata

license: cc-by-nc-4.0
task_categories:
  - other
tags:
  - gesture-recognition
  - action-recognition
  - multimodal
  - IMU
  - video
size_categories:
  - 100K<n<1M

Directory Structure

Published data is organized by collection batch ID.

HiSync_publish/
├── 1/ # Batch ID
│   ├── user1_20250726_132447/ # Sample directory
│   │   ├── cam_1/
│   │   ├── cam_2/
│   │   ├── cam_3/
│   │   ├── person_keypoints.json
│   │   └── meta.json
│   ├── user2_20250726_135244/
│   │   └── ...
│   └── IMU/
│       ├── IMU_Palm/
│       │   └── *.csv
│       ├── IMU_Ring/
│       │   └── *.csv
│       └── IMU_Wrist/
│           └── *.csv
├── 2/
│   └── ...
└── 18/
    └── ...

Notes:

1. Each sample directory is named userX_YYYYMMDD_HHMMSS.
2. Each sample directory contains camera data, person_keypoints.json, and meta.json.
3. IMU data is aggregated per batch under batch_id/IMU/IMU_{Palm|Ring|Wrist}, not in individual sample directories.

Data Format

Example meta.json for a sample:

{
    "user": "user10",
    "action": "Right",
    "perspective": "Eye-level",
    "distance": "10-15m",
    "camera": {
        "cam_0": "telephone",
        "cam_2": "iphone",
        "cam_1": "cam"
    },
    "IMU": {
        "Palm": {
            "timestamp": "5/IMU/IMU_Palm/calibrated_imu_20250727_150254.csv"
        },
        "Ring": {
            "timestamp": "5/IMU/IMU_Ring/calibrated_imu_20250727_150254.csv"
        },
        "Wrist": {
            "timestamp": "5/IMU/IMU_Wrist/calibrated_imu_20250727_150254.csv"
        }
    }
}

Field Constraints:

1. action is standardized to: Right, Left, Approach, Retreat, Summon, Ascend, Descend, No-Gesture.
2. perspective is standardized to: Upward, Eye-level, Downward.
3. distance is standardized as range strings: 3-5m, 5-10m, 10-15m, 15-20m, 20-25m, 25-34m.
4. IMU.*.timestamp may be null; handle null values during parsing.

A small portion of the data may have missing camera or IMU modalities. Ensure robust error handling during reading.

Example person_keypoints.json:

{
    "0": [
        {
            "frame_idx": 0,
            "filename": "frame_0000.png",
            "keypoints": [
                [1204.31, 181.52, 0.9949],
                [1208.77, 170.23, 0.9781],
                [1198.12, 170.84, 0.9675],
                [1216.43, 181.65, 0.8360],
                [1187.55, 183.20, 0.6951]
            ],
            "bbox": [1133, 106, 1373, 813]
        },
        {
            "frame_idx": 1,
            "filename": "frame_0001.png",
            "keypoints": [
                [1204.88, 181.46, 0.9955],
                [1209.06, 170.34, 0.9761],
                [1197.93, 170.95, 0.9748]
            ],
            "bbox": [1132, 106, 1374, 813]
        }
    ],
    "1": [
        {
            "frame_idx": 0,
            "filename": "frame_0000.png",
            "keypoints": [],
            "bbox": [0, 0, 0, 0]
        }
    ]
}

Notes:

1. Top-level keys (e.g., "0", "1") represent person IDs (string format).
2. Each camera corresponds to a frame list with elements containing frame_idx, filename, keypoints, and bbox.
3. Each point in keypoints is [x, y, score], following COCO-17 order.
4. When no person is detected in a frame, keypoints may be an empty array; handle this during parsing.