Batziou Elissavet
Michail Emmanouil
Avgerinakis Konstantinos
Vrochidis Stefanos
Patras Ioannis
Kompatsiaris Ioannis
2018-10-17
<p>This work reports the methodology that CERTH-ITI team developed so as to recognize the emotional impact that movies have to its viewers in terms of valence/arousal and fear. More Specifically,deep convolutional neural networks and several machine learning techniques are utilized to extract visual features and classify them based on the predicted model, while audio features are also taken into account in the fear scenario, leading to highly accurate recognition rates.</p>
https://doi.org/10.5281/zenodo.3491644
oai:zenodo.org:3491644
Zenodo
https://arxiv.org/abs/arXiv:1909.01763
https://zenodo.org/communities/m4d
https://doi.org/10.5281/zenodo.3491643
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
MediaEval, emotion detection, movies video, Visual and audio analysis
Visual and audio analysis of movies video for emotion detection@ Emotional Impact of Movies task MediaEval 2018
info:eu-repo/semantics/workingPaper