https://github.com/hofbi/vibromaf

Automated Quality Assessment for Compressed Vibrotactile Signals Using Multi-Method Assessment Fusion
https://github.com/hofbi/vibromaf

haptics metrics quality-assessment tum vibrotactile

Last synced: 16 days ago
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Automated Quality Assessment for Compressed Vibrotactile Signals Using Multi-Method Assessment Fusion

• Host: GitHub
• URL: https://github.com/hofbi/vibromaf
• Owner: hofbi
• License: mit
• Created: 2022-01-20T13:05:45.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2025-04-08T06:55:07.000Z (19 days ago)
• Last Synced: 2025-04-08T07:38:36.908Z (19 days ago)
• Topics: haptics, metrics, quality-assessment, tum, vibrotactile
• Language: Python
• Homepage: https://hofbi.github.io/vibromaf/
• Size: 517 KB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.md

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README

        
# VibroMAF - Vibrotactile Multi-Method Assessment Fusion

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[![PyPI](https://img.shields.io/pypi/v/vibromaf)](https://pypi.org/project/vibromaf/)

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## Vibrotactile Quality Metrics

This package provides implementations of existing vibrotactile quality metrics and machine learning approach that fuses the individual metric scores into a single final quality score.

## Installation

Install `vibromaf` from [PyPI](https://pypi.org/project/vibromaf):

```shell

pip install vibromaf

```

For development versions and alternative installations see the [installation documentation](https://hofbi.github.io/vibromaf/installation/).

## Usage

- [Get Started](https://hofbi.github.io/vibromaf/get-started/)

- [Full Documentation](https://hofbi.github.io/vibromaf/)

## Citation

If you use this work, please cite our paper ([PDF](https://www.researchgate.net/publication/357556145_Automated_Quality_Assessment_for_Compressed_Vibrotactile_Signals_Using_Multi-Method_Assessment_Fusion))

```tex

@inproceedings{noll_vibromaf,

  author    = {Noll, Andreas and Hofbauer, Markus and Muschter, Evelyn and Li, Shu-Chen and Steinbach, Eckehard},

  booktitle = {2022 IEEE Haptics Symposium (HAPTICS)},

  title     = {Automated Quality Assessment for Compressed Vibrotactile Signals Using Multi-Method Assessment Fusion},

  year      = {2022},

  volume    = {},

  number    = {},

  pages     = {1-6},

  doi       = {10.1109/HAPTICS52432.2022.9765599},

  address   = {Santa Barabara, California, USA}

}

```

## Contribute

See our [CONTRIBUTING.md](CONTRIBUTING.md)