Objective: To design a method for extracting dynamic and static information of the pupil and to establish a database of pupil dynamic and static information in a healthy population. Methods: From January to July 2023, subjects without any ocular or systemic diseases were recruited from the ophthalmology outpatient department. An industrial-grade infrared camera, paired with an 850nm infrared light source, was used to record 20-second videos of the pupil area of each subject. Horizontal pupil diameter data was extracted and saved as txt files. The data was analyzed using R software to construct fitted lines of peaks and troughs during the pupil constriction and dilation process, and the frequency of pupil contraction and dilation was estimated. Results: Pupil dynamic data was collected from 32 subjects with an age range of 7 to 61 years, of whom 50% were male. The spherical equivalent range was from +5.00 D to -5.625 D. The average number of pupil contractions and dilations within the 20-second recordings was (15 ± 7) cycles. Based on the trend of fitted lines for peaks and troughs, pupil dynamic types were categorized into three types: dilation type, stable type, and contraction type. The stable type was further divided into stable dilation, stable constant, and stable contraction subtypes. 25 subjects exhibiting the constriction type. A paired t-test showed no significant difference in the slope and intercept of the fitted lines for peaks and troughs between both eyes. Conclusion: Low-cost and simple equipment combined with algorithms can efficiently and quickly extract dynamic and static pupil information.