Ινστιτούτο Τεχνολογιών Πληροφορικής και Επικοινωνιών

el en

Δημοσιεύσεις Ι.Π.ΤΗΛ.

Affective State Recognition based on Eye Gaze Analysis using Two-Stream Convolutional Networks

In this paper, we propose a novel technique that combines the concept of spatially targeted optical flow with image processing, for affect state recognition, concerning a wide variety of learner types, including children with autism and mainstream children. We exploit the advantages of deep Neural Networks on image classification, by adopting a two–stream CNN approach for the recognition task, based on gaze analysis. As there is not a publicly available dataset to contain such a variety of learner types, a dataset was created in order to evaluate the performance of our algorithm. We validate our approach using this dataset, by optimising a mean–square error loss function, obtaining promising results for this challenging task.

Συνημμένα

  • Affective State Recognition based on Eye Gaze Analysis using Two-Stream Convolutional Networks (529KB)

Ινστιτούτο Τεχνολογιών Πληροφορικής και Επικοινωνιών

Τ.Θ.60361, 6ο χλμ Χαριλάου - Θέρμης, 57001, Θεσσαλονίκη
τηλ. 2311 257701-3 / fax. 2310 474128
email: