Browsing Comunicaciones y ponencias de congresos DIEC - IEKS Biltzarretako komunikazioak eta txostenak by UPNA Author "Porta Cuéllar, Sonia"
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Gaze estimation problem tackled through synthetic images
Garde Lecumberri, Gonzalo
; Larumbe Bergera, Andoni 
; Bossavit, Benoît ; Cabeza Laguna, Rafael ; Porta Cuéllar, Sonia ; Villanueva Larre, Arantxa (Association for Computing Machinery (ACM), 2020)
Contribución a congreso / Biltzarrerako ekarpena 
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 ... -
Introducing I2Head database
Martinikorena Aranburu, Ion ; Cabeza Laguna, Rafael ; Villanueva Larre, Arantxa ; Porta Cuéllar, Sonia (ACM (Association for Computing Machinery), 2018)
Contribución a congreso / Biltzarrerako ekarpena
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 ... -
SeTA: semiautomatic tool for annotation of eye tracking images
Larumbe Bergera, Andoni ; Porta Cuéllar, Sonia ; Cabeza Laguna, Rafael ; Villanueva Larre, Arantxa (ACM, 2019)
Contribución a congreso / Biltzarrerako ekarpena
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
Porta Cuéllar, Sonia ; Bossavit, Benoît ; Cabeza Laguna, Rafael ; Larumbe Bergera, Andoni ; Garde Lecumberri, Gonzalo ; Villanueva Larre, Arantxa (IEEE, 2019)
Contribución a congreso / Biltzarrerako ekarpena
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 ...
