Detecting decision ambiguity from facial images
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00324063" target="_blank" >RIV/68407700:21230/18:00324063 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21240/18:00324063
Result on the web
<a href="http://cmp.felk.cvut.cz/ftp/articles/cech/Jahoda-FG-2018.pdf" target="_blank" >http://cmp.felk.cvut.cz/ftp/articles/cech/Jahoda-FG-2018.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/FG.2018.00080" target="_blank" >10.1109/FG.2018.00080</a>
Alternative languages
Result language
angličtina
Original language name
Detecting decision ambiguity from facial images
Original language description
In situations when potentially costly decisions are being made, faces of people tend to reflect a level of certainty about the appropriateness of the chosen decision. This fact is known from the psychological literature. In the paper, we propose a method that uses facial images for automatic detection of the decision ambiguity state of a subject. To train and test the method, we collected a large-scale dataset from "Who Wants to Be a Millionaire?" -- a popular TV game show. The videos provide examples of various mental states of contestants, including uncertainty, doubts and hesitation. The annotation of the videos is done automatically from on-screen graphics. The problem of detecting decision ambiguity is formulated as binary classification. Video-clips where a contestant asks for help (audience, friend, 50:50) are considered as positive samples; if he (she) replies directly as negative ones. We propose a baseline method combining a deep convolutional neural network with an SVM. The method has an error rate of 24%. The error of human volunteers on the same dataset is 45%, close to chance.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
FG 2018: Proceedings of the 13th IEEE International Conference on Automatic Face & Gesture Recognition
ISBN
978-1-5386-2335-0
ISSN
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e-ISSN
2326-5396
Number of pages
5
Pages from-to
499-503
Publisher name
IEEE
Place of publication
Piscataway
Event location
Xi’an
Event date
May 15, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000454996700070