Neural Networks for Emotion Recognition Based on Eye Tracking Data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86099096" target="_blank" >RIV/61989100:27240/15:86099096 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/document/7379592/" target="_blank" >http://ieeexplore.ieee.org/document/7379592/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SMC.2015.460" target="_blank" >10.1109/SMC.2015.460</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Neural Networks for Emotion Recognition Based on Eye Tracking Data

Popis výsledku v původním jazyce

We present an approach for emotion recognition using information of the pupil. In last years, the pupil variables have been used as an assessment of emotional arousal. In this article, we generate signals of pupil size and gaze position monitored during image viewing. The emotions are provoked by visual stimuli of colored images. Those images were taken from the International Affective Picture System which has been the reference for objective emotional assessment based on visual stimuli. For recognising the emotions we use the evolution of the eye tracking data during a window of time. The learning dataset is composed by the evolution of the pupil size and the gaze position, and labels associated to the emotional states. We study two kinds of learning tools based on Neural Networks. We obtain promising empirical results that show the potential of using temporal learning tools for emotion recognition. (C) 2015 IEEE.

Název v anglickém jazyce

Neural Networks for Emotion Recognition Based on Eye Tracking Data

Popis výsledku anglicky

We present an approach for emotion recognition using information of the pupil. In last years, the pupil variables have been used as an assessment of emotional arousal. In this article, we generate signals of pupil size and gaze position monitored during image viewing. The emotions are provoked by visual stimuli of colored images. Those images were taken from the International Affective Picture System which has been the reference for objective emotional assessment based on visual stimuli. For recognising the emotions we use the evolution of the eye tracking data during a window of time. The learning dataset is composed by the evolution of the pupil size and the gaze position, and labels associated to the emotional states. We study two kinds of learning tools based on Neural Networks. We obtain promising empirical results that show the potential of using temporal learning tools for emotion recognition. (C) 2015 IEEE.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

IEEE International conference on systems, man, and cybernetics, SMC 2015 : proceedings

ISBN

978-1-4799-8697-2

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

2632-2637

Název nakladatele

IEEE Computer Society

Místo vydání

Los Alamitos

Místo konání akce

Hongkong

Datum konání akce

9. 10. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000368940202126