Tunç, YeşimSezgin, Nurdan2025-01-232025-01-232024https://dspace.ankara.edu.tr/handle/20.500.12575/92029Number of studies that are focused on estimating age from facial images are increasing every day. These studies are performed largely by automatic systems. Altough these techniques have given better results, they have not reached successful estimation levels as human made, yet. Being able to identify the significant decision-making variables that influence people's estimations is one of the things that can improve these systems. The aim of this study is to examine the success rate of human observers' estimations and to draw attention to what affects those estimations. In this study an age estimation survey was offered; people were asked whether they trust themselves about age estimation and which factors affect their estimations. Participants have been provided with an online survey created using Google Forms. A total of 223 people participated in the study, 66 male and 157 female. In general total 5 images were estimated correctly out of 12, 7 were estimated incorrectly. The ages of all participants (face images of 12 individuals) were estimated correctly with an average of 30.08%. The majority of participants (77,6%) claim to trust their judgement on some level and to make correct estimations overall. When the frequency of factor designation was examined, it was discovered that the majority of participants (65,17%) were focused on the wrinkles on faces (the study includes general face, eyes and mouth.). It is expected that future studies would yield improved results by increasing the number of factors affecting age estimation and including more machine learning studies.trAge EstimationEstimation AbilityIdentificationSkin AgingWrinkleArticle