  In this work, we introduce EyeDentify, a dataset specifically designed for
pupil diameter estimation based on webcam images. EyeDentify addresses the lack
of available datasets for pupil diameter estimation, a crucial domain for
understanding physiological and psychological states traditionally dominated by
highly specialized sensor systems such as Tobii. Unlike these advanced sensor
systems and associated costs, webcam images are more commonly found in
practice. Yet, deep learning models that can estimate pupil diameters using
standard webcam data are scarce. By providing a dataset of cropped eye images
alongside corresponding pupil diameter information, EyeDentify enables the
development and refinement of models designed specifically for less-equipped
environments, democratizing pupil diameter estimation by making it more
accessible and broadly applicable, which in turn contributes to multiple
domains of understanding human activity and supporting healthcare. Our dataset
is available at https://vijulshah.github.io/eyedentify/.
