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Gaze estimation problem tackled through synthetic images
(Association for Computing Machinery (ACM), 2020)
info:eu-repo/semantics/conferenceObject,
In this paper, we evaluate a synthetic framework to be used in the field of gaze estimation employing deep learning techniques. The lack of sufficient annotated data could be overcome by the utilization of a synthetic ...
SeTA: semiautomatic tool for annotation of eye tracking images
(ACM, 2019)
info:eu-repo/semantics/conferenceObject,
Availability of large scale tagged datasets is a must in the field of deep learning applied to the eye tracking challenge. In this paper, the potential of Supervised-Descent-Method (SDM) as a semiautomatic labelling tool ...
U2Eyes: a binocular dataset for eye tracking and gaze estimation
(IEEE, 2019)
info:eu-repo/semantics/conferenceObject,
Theory shows that huge amount of labelled data are needed in order to achieve reliable classification/regression methods when using deep/machine learning techniques. However, in the eye tracking field, manual annotation ...
Introducing I2Head database
(ACM (Association for Computing Machinery), 2018)
info:eu-repo/semantics/conferenceObject,
I2Head database has been created with the aim to become an optimal reference for low cost gaze estimation. It exhibits the following outstanding characteristics: it takes into account key aspects of low resolution eye ...