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---
license: mit
task_categories:
- video-classification
- zero-shot-classification
tags:
- motion-detection
- temporal-vision
- speckle-noise
size_categories:
- n<1K
---
# Motion-Text Classifier Dataset
A binary classification dataset for distinguishing between pure motion and text-revealed-through-motion in speckle noise videos.
## Dataset Description
This dataset contains 1000 videos (5 seconds each) designed to test motion-based perception:
- **Motion-only (500 videos)**: Pure background noise scrolling horizontally
- **Text videos (500 videos)**: Single words revealed through opposing foreground/background motion
All videos use identical noise parameters to ensure the **only** distinguishing feature is the presence of foreground content.
## Dataset Structure
```
dataset/
├── train/
│ ├── motion_0000.mp4 to motion_0449.mp4 (450 videos)
│ ├── text_0000.mp4 to text_0449.mp4 (450 videos)
│ └── metadata.csv
└── test/
├── motion_0450.mp4 to motion_0499.mp4 (50 videos)
├── text_0450.mp4 to text_0499.mp4 (50 videos)
└── metadata.csv
```
## Usage
```python
from datasets import load_dataset
# Load dataset
dataset = load_dataset("mukul54/motion-text-classifier")
# Access samples
train_sample = dataset['train'][0]
print(train_sample['label']) # 'motion_only' or 'text_fg_bg'
print(train_sample['text']) # word shown (None for motion_only)
```
## Video Parameters
All videos share identical generation parameters:
| Parameter | Value |
|-----------|-------|
| Resolution | 960×540 |
| FPS | 60 |
| Duration | 5.0 seconds |
| Noise Density | 0.5 |
| Speckle Size | 1 |
| Speed | 2 |
| Direction | Horizontal |
## Labels
- **motion_only**: Background noise only (no foreground object)
- **text_fg_bg**: Text revealed through opposite motion of foreground/background using the same noise pattern
## Key Features
- **Pure motion detection**: Text is invisible in static frames
- **Controlled experiment**: All parameters identical except foreground content
- **Temporal encoding**: Information only available through motion analysis
## Use Cases
- Testing motion perception in vision models
- Temporal feature extraction benchmarks
- Zero-shot video understanding
- Motion-based object detection
## Citation
If you use this dataset, please cite:
```bibtex
@dataset{motion_text_classifier,
title={Motion-Text Classifier: Speckle Noise Motion Detection Dataset},
author={Mukul},
year={2025},
publisher={HuggingFace},
url={https://huggingface.co/datasets/mukul54/motion-text-classifier}
}
```
## License
MIT License
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