task_categories:object-detection license:mit size_categories:1K<n<10K format:imagefolder modality:image modality:text library:datasets library:mlcroissant region:us thermal human pose estimation
---
license: mit
task_categories:
- object-detection
tags:
- thermal human pose estimation
pretty_name: otp
size_categories:
- 1K<n<10K
---
# OpenThermalPose: An Open-Source Annotated Thermal Human Pose Dataset
**Paper:** [OpenThermalPose: An Open-Source Annotated Thermal Human Pose Dataset and Initial YOLOv8-Pose Baselines](https://ieeexplore.ieee.org/document/10581992)

**GitHub:** [https://github.com/IS2AI/OpenThermalPose](https://github.com/IS2AI/OpenThermalPose)

**Description:** The OpenThermalPose dataset provides 6,090 images of 31 subjects and 14,315 annotated human instances. Annotations include bounding boxes and 17 anatomical keypoints, following the conventions used in the benchmark MS COCO Keypoint dataset. The dataset covers various fitness exercises, multiple-person activities, and outdoor walking in different locations under different weather conditions. 
As a baseline, we trained and evaluated the YOLOv8-pose models (nano, small, medium, large, and x-large) on this dataset. The pre-trained models are available at our GitHub repository.
![image/png](https://github.com/IS2AI/OpenThermalPose/raw/main/3370.png)

**Citation:**
```bibtex
@INPROCEEDINGS{10581992,
  author={Kuzdeuov, Askat and Taratynova, Darya and Tleuliyev, Alim and Varol, Huseyin Atakan},
  booktitle={2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG)}, 
  title={OpenThermalPose: An Open-Source Annotated Thermal Human Pose Dataset and Initial YOLOv8-Pose Baselines}, 
  year={2024},
  volume={},
  number={},
  pages={1-8},
  keywords={Privacy;Annotations;Source coding;Pose estimation;Lighting;Medical services;Motion capture},
  doi={10.1109/FG59268.2024.10581992}}

```

