Classification of Eye Images by Personal Details With Transfer Learning Algorithms

During the data collection phase of the research, first of all, a brief information was given to the participants about the study, and how the data would be used and what to do. Photographs of the eye area were collected from participants consisting of a total of 96 different people aged between 3-64. It has been clearly stated that there will be no situations that will define them during the photo shoot. Then, at least ten images of the right eye area of each person were taken. In addition, at least ten photographs of the left eye area were taken. Along with these photographs, no data other than the age and gender of the persons was recorded. Below are images of two people of different genders.

A total of 1980 images were obtained from the participants, as in the figure above. More than ten images were obtained from some people. For this reason, there is a difference in the number of photos of people. Care has been taken to use different angles and lights so that each photograph does not form the same frame. Thus, photographs that were not, all the same, were collected. In order for each photograph not to be confused with another photograph, a naming rule has been developed to express the person, age, gender and the number of the photograph taken. An underscore ("_") character is inserted between each expression. Each expression used in the naming convention is given below in order.

Person ID: It is a unique code value for each person photographed. This value ranges from 1 to 100.

Age: The age is written directly as a number to express how old the person is. This value varies between 3-64.

Gender ID: The value of 1 is expressed if the person photographed is male, and the value of 0 if it is a woman.

Photo ID: Due to the fact that more than one photo was taken for each person, each photo was numbered sequentially from 1-10.

If this dataset is used, reference should be made to the article below.

Aktürk, C., Aydemir, E., Hama Rashid, Y. M. 2022. Classification of eye images according to person details with the transfer learning algorithms. Acta Informatica Pragensia, DOI: 10.18267/j.aip.190