dc.contributor.author | Christensen, Kristoffer Moberg | |
dc.date.accessioned | 2018-09-19T06:56:00Z | |
dc.date.available | 2018-09-19T06:56:00Z | |
dc.date.issued | 2018 | |
dc.identifier.uri | http://hdl.handle.net/11250/2563318 | |
dc.description | Master's thesis Information- and communication technology IKT590 - University of Agder 2018 | nb_NO |
dc.description.abstract | This thesis proposes a way to simplify and make solutions for spontaneous and
posed facial expression analysis more efficient. Traditional approaches have been
using hand-crafted features and two image frames to be able to differentiate between
spontaneous and posed facial expressions. The solution aims to be as flexible
as possible and introduces two models to differentiate between posed and
spontaneous facial expression.
We introduce Inception V4 as an algorithm to solve this task. The results
indicate that Inception V4 may be too deep and unable to differentiate between
spontaneous and posed facial expression accurately. A shallow CNN model is
also introduced. The shallow CNN model performs better than the Inception V4
model. None of the two come close to the state-of-the-art results. This may
indicate that to differentiate between spontaneous and posed facial expressions
the difference between the onset and apex frame of an expression is needed as
input. This thesis, also suggests an alternative algorithm based on our findings.
For further work, an algorithm which is not as deep as Inception V4 is needed.
However, by using parts of the Inception V4 architecture, we may be able to
capture facial features better.
The task of differentiating between spontaneous emotion and posed emotion
has also been investigated; however, the results do not show great promise. The
task does not have any state-of-the-art results to compare our approach with. Our
models, although lacking in performance, does seem able to capture relevant facial
features from the dataset. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Universitetet i Agder ; University of Agder | nb_NO |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.subject | IKT590 | nb_NO |
dc.title | Differentiating Between Spontaneous and Posed Facial Expression using Inception V4 | nb_NO |
dc.type | Master thesis | nb_NO |
dc.subject.nsi | VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550 | nb_NO |
dc.source.pagenumber | 70 p. | nb_NO |