Dataset for the evaluation of eye detector for gaze estimation
Victoria Ponz, Arantxa Villanueva, Rafael Cabeza · 2012
Being able to perform eye tracking with low cost technology is the key to broaden its applications and one of the major goals for the eye tracking community nowadays. Furthermore, new datasets to evaluate the different methods are needed to reproduce the real conditions in which these algorithms work. In this paper, we present a dataset containing images of subjects with different gaze orientations as a new evaluation tool. First step in eye tracking algorithms is to detect the region of the eyes, and using the Gi4e dataset, we evaluate the best performing public Haar based classifiers under different gaze orientations to detect the eye area, proving this dataset to be a fair evaluation method.