JeFaPaTo -- A joint toolbox for blinking analysis and facial features
  extraction
Tim Büchner Oliver Mothes Orlando Guntinas-Lichius Joachim Denzler
Analyzing facial features and expressions is a complex task in computer
vision. The human face is intricate, with significant shape, texture, and
appearance variations. In medical contexts, facial structures that differ from
the norm, such as those affected by paralysis, are particularly important to
study and require precise analysis. One area of interest is the subtle
movements involved in blinking, a process that is not yet fully understood and
needs high-resolution, time-specific analysis for detailed understanding.
However, a significant challenge is that many advanced computer vision
techniques demand programming skills, making them less accessible to medical
professionals who may not have these skills. The Jena Facial Palsy Toolbox
(JeFaPaTo) has been developed to bridge this gap. It utilizes cutting-edge
computer vision algorithms and offers a user-friendly interface for those
without programming expertise. This toolbox is designed to make advanced facial
analysis more accessible to medical experts, simplifying integration into their
workflow.
  The state of the eye closure is of high interest to medical experts, e.g., in
the context of facial palsy or Parkinson's disease. Due to facial nerve damage,
the eye-closing process might be impaired and could lead to many undesirable
side effects. Hence, more than a simple distinction between open and closed
eyes is required for a detailed analysis. Factors such as duration,
synchronicity, velocity, complete closure, the time between blinks, and
frequency over time are highly relevant. Such detailed analysis could help
medical experts better understand the blinking process, its deviations, and
possible treatments for better eye care.