ONEPAGER.md

Quality Vision — Hand Motion Dataset

Train your AI on real hand motion data — ready in minutes.

Unlike many academic datasets, Quality Vision B2B exports are intended for commercial use under your agreed license terms — see LICENSE_EXPORT.txt in the ZIP and manifest.license / dataset_license (not limited to research-only).

1. Features

• 21-point hand keypoints (MediaPipe-style)
• Temporal sequences with timestamps
• Per-frame action field + metadata/actions.csv (optional per-frame taxonomy via job payload)
• Hand–object interaction metadata when hq.object_interaction is configured
• Optional camera_pov: first_person | third_person (manual)
• JSONL + optional COCO-like keypoints export
• PyTorch loader guide: examples/README_PYTORCH.md

2. Use cases

• 🤖 Robotics
• 🥽 AR/VR
• ✋ Gesture recognition
• 🧠 Human behavior AI

3. What's inside (dataset/)

dataset/
├── data.jsonl
├── metadata/
│   ├── actions.csv
│   └── dataset_meta.json
├── per_video/
├── features.json
├── global_stats.json   # includes buyer_marketing for hand jobs
└── examples/
    └── README_PYTORCH.md

Dataset snapshot (metrics)

• Job ID: bulk_9_videos_933d5ad5
• Action label: Dexterous Hand movements
• Videos processed: 9
• Exported frames (HQ, incl. augmentations): 9112
• Accepted frames (pre-augmentation): 2278
• Sampled candidate frames: 3962
• Rejected frames: 1684
• Acceptance rate (pre-aug / sampled): 57.5%

Quality Metrics (Accepted Frames)

• Mean quality score: 0.9715
• Mean landmark visibility: 0.9430
• Mean lower-body visibility: 0.0000
• Mean motion_local: 1.0000

Processing

• Gaussian temporal smoothing: window=5 (x/y/z only; visibility not smoothed)
• Keypoints: MediaPipe Hands (21 landmarks per frame when detected)
• Dexterous block: finger_angles_deg, grip_type_proxy, tip velocities, hand_visibility_mean, dexterous_quality_proxy, hand motion_intelligence (v3)
• Augmentations: horizontal flip + keypoint noise
• Motion intelligence: hand-centric (v3) — wrist speed, finger-tip motion, grip heuristic, activity class

Hand motion intelligence (dexterous)

• Mean finger-tip speed: 0.6318
• Mean wrist speed (norm/sec): 0.4500
• Frames with hand MI: 2278
• Hand activity histogram: {"finger_active": 2240, "hand_translating": 1, "manipulation": 24, "static": 13}
• Grip type histogram: {"neutral": 3, "open": 1444, "pinch": 227, "power": 33, "precision": 571}

Deliverables (inside this ZIP)

• data.jsonl
• per_video/video_*.jsonl
• per_video/rejected_*.jsonl
• features.json
• export_quality_report.json
• manifest.json
• global_stats.json
• runtime_config.json
• SCHEMA.md
• examples/
• examples/sample_rows_accepted.jsonl
• examples/sample_rows_rejected.jsonl
• examples/sample_features.json
• examples/LOAD_EXAMPLE.py
• examples/README_PYTORCH.md
• metadata/actions.csv
• metadata/dataset_meta.json
• SHA256SUMS

Quality Score Definition

• Per frame: frame_quality_score = 0.5 * avg_landmark_visibility + 0.0 * lower_body_visibility + 0.5 * motion_local.

https://qvision.space/