@article{buechner2024jefapato,
    type = {article},
    key = {buechner2024jefapato},
    title = {JeFaPaTo - A Joint Toolbox for Blinking Analysis and Facial Features Extraction},
    author = {Tim Büchner and Oliver Mothes and Orlando Guntinas-Lichius and Joachim Denzler},
    year = {2024},
    month = {may},
    journal = {Journal of Open Source Software},
    publisher = {The Open Journal},
    volume = {9},
    number = {97},
    pages = {6425},
    doi = {10.21105/joss.06425},
    url = {},
    code = {https://github.com/cvjena/JeFaPaTo},
    abstract = {Welcome to JeFaPaTo, the Jena Facial Palsy Tool! This powerful tool is designed to assist in various medical and psychological applications by providing accurate facial feature extraction and analysis. It combines the requirements of a medical environment with the possibilities of modern computer vision and machine learning. Our goal is to allow medical professionals to use state-of-the-art technology without needing to write custom algorithms. We provide the libraries and an interface to the commonly used mediapipe library of Google, a powerful tool for facial landmark extraction, and now even offers the distinction into facial movements. Additionally, our software can be extended to include new methods and algorithms. We are interested in human blinking behavior and scrutinize it with high temporal videos using the EAR-Score (Eye-Aspect-Ratio) to detect blinking and eye closure. This feature is used to analyze patients with facial palsy blinking behavior.  },
}