Datasets:

standard-cognition
/

Tracks

@@ -1,94 +1,96 @@
----
-pretty_name: Tracks
-license: cc-by-4.0
-tags:
-  - computer-vision
-  - human-motion
-  - robotics
-  - trajectory
-  - pose-estimation
-  - navigation
-  - retail
-task_categories:
-  - image-feature-extraction
-  - keypoint-detection
-  - object-detection
-  - image-segmentation
-  - reinforcement-learning
-size_categories:
-  - 1M<n<100M
----
-# Tracks Dataset
-**Real Human Motion for Robotics Planning and Simulation**
----
-## Overview
-<video src="https://huggingface.co/datasets/standard-cognition/Tracks/resolve/main/assets/visual.mp4"
-       autoplay
-       loop
-       muted
-       playsinline
-       style="width:100%;height:auto;border-radius:8px;">
-  Your browser does not support the video tag.
-</video>
-The **Tracks Dataset** captures continuous, real-world human movement in retail environments, providing one of the largest and most structured pose-based trajectory corpora available for **robotics** and **embodied AI** research.
-Each record represents **3D pose sequences** sampled at 10 Hz across normalized store coordinates, enabling research in motion planning, human-aware navigation, and humanoid gait learning derived directly from real behavior :contentReference[oaicite:0]{index=0}.
----
-## Key Specifications
-| Field | Description |
-|:------|:-------------|
-| **Source** | Anonymized in-store multi-camera captures (10 retail sites) |
-| **Scope** | ≈ 60,000 hours of human trajectory data (plus 1-hour evaluation subset) |
-| **Format** | CSV schema, ROS 2–compatible via playback plug-in |
-| **Sampling Frequency** | 10 Hz (10 FPS) |
-| **Pose Structure** | 26 keypoints per person per frame (3D coordinates) |
-| **Environment** | Real retail environments with normalized floor layouts |
-| **Evaluation Subset** | One-hour segment including trajectories + store layout |
-| **Key Metrics** | ≈ 2.3 M unique shoppers |
-| **Anonymization** | Face and body suppression; coordinate-only representation |
-| **Governance** | Managed under Standard AI’s data governance policies aligned with GDPR/CCPA and Responsible AI principles |
----
-## Integration & Applications
-- Distributed in **CSV** with schema documentation and import notebooks.
-- Ready for **ROS 2** integration for **path planning** and **human–robot interaction** simulation.
-- Compatible with **Python**, **PyTorch**, and standard **reinforcement-learning** frameworks.
-### Example Research Uses
-- Motion prediction and trajectory planning
-- Reinforcement learning for humanoid gait and control
-- Human-aware navigation and avoidance behavior
-- Simulation of human–robot interaction environments
----
-## Access
-The **Tracks Dataset** is available now for evaluation and licensing.
-- **Evaluation subset:** 1-hour sample under 30-day Evaluation Agreement (private Hugging Face repo).
-- **Full dataset:** 60,000-hour commercial dataset available by request.
-For inquiries or licensing:
-✉️ [[email protected]](mailto:[email protected])
----
-## Citation
-```bibtex
-@dataset{standardlabs_tracks_2025,
-  title        = {Tracks Dataset: Real Human Motion for Robotics Planning and Simulation},
-  author       = {Standard Labs},
-  year         = {2025},
-  publisher    = {Hugging Face},
-  url          = {https://huggingface.co/datasets/standard-labs/tracks}
-}

+---
+pretty_name: Tracks
+license: cc-by-4.0
+tags:
+  - computer-vision
+  - human-motion
+  - robotics
+  - trajectory
+  - pose-estimation
+  - navigation
+  - retail
+task_categories:
+  - image-feature-extraction
+  - keypoint-detection
+  - object-detection
+  - image-segmentation
+  - reinforcement-learning
+size_categories:
+  - 1M<n<100M
+---
+# Tracks Dataset
+**Real Human Motion for Robotics Planning and Simulation**
+**The ros2 docker container compiliation and visualization script instructions can be found here: https://huggingface.co/datasets/standard-cognition/Tracks/blob/main/keypoint-db/README.md**
+---
+## Overview
+<video src="https://huggingface.co/datasets/standard-cognition/Tracks/resolve/main/assets/visual.mp4"
+       autoplay
+       loop
+       muted
+       playsinline
+       style="width:100%;height:auto;border-radius:8px;">
+  Your browser does not support the video tag.
+</video>
+The **Tracks Dataset** captures continuous, real-world human movement in retail environments, providing one of the largest and most structured pose-based trajectory corpora available for **robotics** and **embodied AI** research.
+Each record represents **3D pose sequences** sampled at 10 Hz across normalized store coordinates, enabling research in motion planning, human-aware navigation, and humanoid gait learning derived directly from real behavior :contentReference[oaicite:0]{index=0}.
+---
+## Key Specifications
+| Field | Description |
+|:------|:-------------|
+| **Source** | Anonymized in-store multi-camera captures (10 retail sites) |
+| **Scope** | ≈ 60,000 hours of human trajectory data (plus 1-hour evaluation subset) |
+| **Format** | CSV schema, ROS 2–compatible via playback plug-in |
+| **Sampling Frequency** | 10 Hz (10 FPS) |
+| **Pose Structure** | 26 keypoints per person per frame (3D coordinates) |
+| **Environment** | Real retail environments with normalized floor layouts |
+| **Evaluation Subset** | One-hour segment including trajectories + store layout |
+| **Key Metrics** | ≈ 2.3 M unique shoppers |
+| **Anonymization** | Face and body suppression; coordinate-only representation |
+| **Governance** | Managed under Standard AI’s data governance policies aligned with GDPR/CCPA and Responsible AI principles |
+---
+## Integration & Applications
+- Distributed in **CSV** with schema documentation and import notebooks.
+- Ready for **ROS 2** integration for **path planning** and **human–robot interaction** simulation.
+- Compatible with **Python**, **PyTorch**, and standard **reinforcement-learning** frameworks.
+### Example Research Uses
+- Motion prediction and trajectory planning
+- Reinforcement learning for humanoid gait and control
+- Human-aware navigation and avoidance behavior
+- Simulation of human–robot interaction environments
+---
+## Access
+The **Tracks Dataset** is available now for evaluation and licensing.
+- **Evaluation subset:** 1-hour sample under 30-day Evaluation Agreement (private Hugging Face repo).
+- **Full dataset:** 60,000-hour commercial dataset available by request.
+For inquiries or licensing:
+✉️ [[email protected]](mailto:[email protected])
+---
+## Citation
+```bibtex
+@dataset{standardlabs_tracks_2025,
+  title        = {Tracks Dataset: Real Human Motion for Robotics Planning and Simulation},
+  author       = {Standard Labs},
+  year         = {2025},
+  publisher    = {Hugging Face},
+  url          = {https://huggingface.co/datasets/standard-labs/tracks}
+}