ORION WWF1 — Unified Methodology (Anonymization + Labeling)
1. Overview
The ORION dataset follows a Dual-Engine Pipeline to produce high-fidelity industrial data that is both private and intelligent:
- Anonymization Engine: Guarantees zero-leak privacy (Dual-pass AI + Human Audit).
- Labeling Engine (Adjudicator): Produces multi-layer industrial annotations (HAR, PPE, Scene Graphs).
2. Anonymization Pipeline (Pass 1 & 2)
Refer to the previous sections for the detailed 5-model cascade (YOLOv8, YOLOv11, InsightFace) used for the Dual-Pass Anonymization.
Visual Destruction Standard
- Blur: Gaussian Blur (Kernel 99x99, Sigma 30).
- Expansion: 1.68x safety margin.
- Verification: Secondary scan for residual leaks with Vertical/Horizontal Flip TTA.
3. Industrial Labeling Pipeline (Orion Adjudicator)
Once the video is anonymized, it enters the Adjudicator pipeline for high-level semantic enrichment.
Layer 1 — Human Activity Recognition (HAR)
Activities are labeled using a temporal event model:
- Scope: 44 distinct activity segments across 10 clips.
- Taxonomy: walking, carrying_object, assembling, inspecting, cleaning, operating_machine, standing_idle.
- Precision: Sub-second start/end timestamps.
Layer 2 — Safety Compliance (PPE)
A multi-category safety audit is performed for every agent:
- Categories: Head, Eyes, Hearing, Respiratory, Hands, Body, Legs, Feet.
- States: YES (Compliant), NO (Non-compliant), HIDDEN (Not visible from camera angle).
- Validation: 100% human-verified safety audit reports.
Layer 3 — Physical AI Environment
Scene-level metadata is extracted for robotics and plant optimization:
- Plant Context: Floor type (concrete), Lighting (artificial), estimated area (m²).
- Asset Hierarchy: CNC machine state (Active/Idle), navigation hazards, camera mounting height/angle.
Layer 4 — Object Detection (COCO Format)
To support ML training, keyframes are extracted and annotated:
- Frequency: 1 frame per second (310 total frames).
- Annotations: Bounding boxes in standard COCO JSON format.
- Categories: 1=Worker (Agent), 2=Industrial Machine (Asset).
- Anonymization Consistency: All frames are extracted from blurred video to ensure 100% privacy compliance.
4. Quality & Certification (Level 3)
The Level 3 Certification implies:
- AI Proposition: All detections and labels are initially proposed by specialized AI models.
- Human Adjudication: Trained industrial analysts review and correct every single label.
- Integrity Locking: Final assets are hashed (SHA-256) to prevent tampering.
5. Unified Taxonomy
The dataset uses a strict hierarchy defined in orion_wwf1_taxonomy.json and validated by the orion_wwf1_fields_schema.json to ensure consistency across the entire 622-clip mother dataset.
ORION – Industrial AI Data Lab | Pipeline Version: Orion Unified V5.2