The Method for Visualization and Analysis of Eye-blinking Patterns using Dynamic Vision^*.

Area of Science:

• Biomedical Engineering
• Computer Vision
• Ophthalmology

Background:

• Traditional eye blinking analysis involves comparing consecutive frames, which is time-consuming.
• Existing methods often require complex image processing to isolate eyelid movements.
• Background noise and accessories can complicate the analysis of eye blinking patterns.

Purpose of the Study:

• To propose an efficient method for measuring and visualizing eye blinking patterns.
• To leverage dynamic vision data for simplified and faster eye blinking analysis.
• To develop a technique for clear visualization of eyelid changes during blinking.

Main Methods:

• Utilizing dynamic vision data, which captures only pixels with temporal luminance changes.
• Implementing image processing to remove noise and unnecessary data from the dynamic vision output.
• Estimating the shape and position of the upper eyelid from the processed data.
• Visualizing the dynamic changes of the eyelid during a blinking sequence into a single image.

Main Results:

• Dynamic vision data significantly reduces the time cost associated with analyzing eye blinking.
• Image processing is simplified due to the grayscale nature and reduced data of dynamic vision.
• The method effectively estimates eyelid shape and position.
• The resulting visualization allows for at-a-glance analysis of eye blinking patterns.

Conclusions:

• The proposed method offers an efficient and simplified approach to eye blinking pattern analysis.
• Dynamic vision technology is effective for reducing analysis time and improving visualization clarity.
• This technique facilitates easier and more intuitive understanding of eyelid dynamics.