README.md

---
license: mit
---
---
language:
- en
tags:
- **event-based-vision**
- eye-dataset
- **microsaccade**
- fixation
- **fixational-eye-movements**
size_categories:
- 100K<n<1M
license: cc-by-nc-4.0
---

# C3I-SynMicrosaccade: Microsaccade-benchmark Dataset

The **Microsaccade-benchmark Dataset** is a high-resolution, event-based dataset designed for microsaccade detection, classification, and analysis, developed by researchers at the University of Galway. Microsaccades are small, involuntary eye movements that occur during visual fixation, playing a critical role in vision research, driver monitoring systems (DMS), neuromorphic vision, and eye-tracking applications. This dataset provides both raw rendered data (RGB images, annotations(yaw, pitch, roll)) and preprocessed training-ready `.npy` event streams to support the development of event-based neural networks and other algorithms for modeling fine-grained, high-temporal-resolution eye movement patterns.  

This dataset was introduced in a paper accepted at **BMVC 2025**.

![Microsaccade Event Example](https://huggingface.co/datasets/waseemshariff/Microsaccade-benchmark/resolve/main/misc/ms.gif)

---

## Dataset Structure

The dataset is organized into two sections: **RGB Microsaccade Sequences** and **Event Microsaccade Sequences**.

### **1. RGB Microsaccade Sequences**

Each microsaccade class contains **500 sequences**, with each sequence consisting of a small series of rendered eye frames and their corresponding annotations (**yaw, pitch, roll**). 

#### Directory Layout

```
RGB/
├── 0.5_left/
│   ├── saccade_0.npz
│   ├── ...
│   └── saccade_499.npz
├── ...
├── 2.0_left/
│   ├── saccade_0.npz
│   ├── ...
│   └── saccade_499.npz
├── 0.5_right/
│   ├── saccade_0.npz
│   ├── ...
│   └── saccade_499.npz
├── ...
└── 2.0_right/
    ├── saccade_0.npz
    ├── ...
    └── saccade_499.npz
```

*See Figure \ref{fig:dir_rgb_microsaccades} for a schematic.*

---

### **2. Event Microsaccade Sequences**

Preprocessed `.npy` files organized into **Train/Validation, and Test sets** for left and right eyes. Each folder contains seven classes corresponding to microsaccade amplitudes from **0.5° to 2.0°**, with 17500 (Train/Validation) and 300 (Test) samples in each. 

#### Directory Layout
```
Events/
├── train_and_validate/
│   ├── 0.5_left/
│   │   ├── saccade_0_0_0.npy
│   │   ├── ...
│   │   └── saccade_499_4_4.npy
│   ├── ...
│   ├── 2.0_right/
│   │   ├── saccade_0_0_0.npy
│   │   ├── ...
│   │   └── saccade_499_4_4.npy
│   └──left_eye_splits.txt (train-validation splits)
│   └──right_eye_splits.txt (train-validation splits)
│
└── Test/
    ├── 0.5_left/
    │   ├── saccade_0_0_0.npy
    │   ├── ...
    │   └── saccade_59_4_4.npy
    ├── ...
    └── 2.0_right/
        ├── saccade_0_0_0.npy
        ├── ...
        └── saccade_59_4_4.npy
```

*See Figure \ref{fig:dir_event_microsaccades} for a schematic.*

---

## `.npy` File Format

Each `.npy` file contains:

```python
{
   [T, X, Y, P]   # Shape: [N, 4] 
}
Where:

T: Timestamp (seconds)
X: Pixel x-coordinate
Y: Pixel y-coordinate
P: Event polarity (1 = ON, 0 or -1 = OFF)
```

## Dataset Overview
| Property            | Value              |
| ------------------- | ------------------ |
| Original resolution | 800 × 600          |
| ROI resolution      | 440 × 300 (center) |
| Total sequences     | 175,000            |
| Left eye sequences  | 87,500             |
| Right eye sequences | 87,500             |
| Number of classes   | 7                  |


---
## License: cc-by-nc-4.0
This dataset is licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. This license allows for non-commercial use of the dataset, provided proper attribution is given to the authors. Adaptations and modifications are permitted for non-commercial purposes. For full details, please review the CC BY-NC 4.0 license and the license file included in the dataset. As the dataset is gated, you must accept the access conditions on Hugging Face to use it.
---

## Citation

If you use this dataset in your research, please cite the following:

```
@dataset{microsaccade_dataset_2025,
  title={Microsaccade Recognition with Event Cameras: A Novel Dataset},
  author={Waseem Shariff and Timothy Hanley and Maciej Stec and Hossein Javidnia and Peter Corcoran},
  year={2025},
  doi={https://doi.org/10.57967/hf/6965},
publisher={Hugging Face},
  note={Presented at BMVC 2025}
}
@inproceedings{Shariff_2025_BMVC,
author    = {Waseem Shariff and Timothy Hanley and Maciej Stec and Hossein Javidnia and Peter Corcoran},
title     = {Benchmarking Microsaccade Recognition with Event Cameras: A Novel Dataset and Evaluation},
booktitle = {36th British Machine Vision Conference 2025, {BMVC} 2025, Sheffield, UK, November 24-27, 2025},
publisher = {BMVA},
year      = {2025},
url       = {https://bmva-archive.org.uk/bmvc/2025/assets/papers/Paper_288/paper.pdf}
}
@article{microsaccade_benchmarking_2025,
  title={Benchmarking Microsaccade Recognition with Event Cameras: A Novel Dataset and Evaluation},
  author={Shariff, Waseem and Hanley, Timothy and Stec, Maciej and Javidnia, Hossein and Corcoran, Peter},
  journal={arXiv preprint arXiv:2510.24231},
  year={2025}
}

```

## Contact

For questions, updates, or issues, open a discussion or pull request in the Community tab.