RT Journal Article
T1 Emotion and attention: Audiovisual models for group-level skin response recognition in short movies
A1 García Faura, Álvaro
A1 Hernández García, Alejandro
A1 Fernández Martínez, Fernando
A1 Díaz de María, Fernando
A1 San Segundo, Rubén
AB The electrodermal activity (EDA) is a psychophysiological indicator which can be considered a somatic marker of the emotional and attentional reaction of subjects towards stimuli. EDA measurements are not biased by the cognitive process of giving an opinion or a score to characterize the subjective perception, and group-level EDA recordings integrate the reaction of the whole audience, thus reducing the signal noise. This paper contributes to the field of affective video content analysis, extending previous novel work on the use of EDA as ground truth for prediction algorithms. Here, we label short video clips according to the audience's emotion (high vs. low) and attention (increasing vs. decreasing), derived from EDA records. Then, we propose a set of low-level audiovisual descriptors and train binary classifiers that predict the emotion and attention with 75% and 80% accuracy, respectively. These results, along with those of previous works, reinforce the usefulness of such low-level audiovisual descriptors to model video in terms of the induced affective response.
PB IOS
SN 2405-6456
YR 2019
FD 2019-02-22
LK https://hdl.handle.net/10016/30807
UL https://hdl.handle.net/10016/30807
LA eng
NO The work leading to these results has been supported by ESITUR (MINECO, RTC-2016-5305-7), CAVIAR (MINECO, TEC2017-84593-C2-1-R), and AMIC (MINECO, TIN2017-85854-C4-4-R) projects (AEI/FEDER, UE). We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan X Pascal GPU used for this research.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641805.
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RD 19 may. 2024