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Metodología para Detección de Características Faciales con Fines de Reconocimiento de Emociones

Authors: Gonzalez, C.; Rincon, S.; Quintero, O.L.; Restrepo, R.;

Metodología para Detección de Características Faciales con Fines de Reconocimiento de Emociones

Abstract

Se cree que la detección de emociones podrá llevar a determinar el estado de _animo de una persona e incluso un posible fraude. La detección de rasgos faciales claves para la detección de una emoción son de fácil reconocimiento para los humanos, pero la dificultad crece cuando se realiza por medio de software. Por este motivo, la presente investigación aborda el problema de detección mediante varias técnicas, identificando una en especial basada en las proporciones _áureas la cual robustece la detección de rasgos faciales y por consiguiente la detección de la emoción; guardando siempre unas medidas de incertidumbre racionales.

It is believed that the detection of emotions could lead to determine the mood of a person or even a possible fraud. The detection of key facial features to detect emotions are of easy recognition for humans, but the diffculty increases when is done by software. For this reason, this investigation addresses the problem of detection of emotions through several techniques, identifying one in particular based on the golden proportions, which strengthens the detection of facial features and therefore the detection of emotion, keeping rational measures of uncertainty.

Country
Colombia
Related Organizations
Keywords

Viola-Jones, Canon, detección, optimización de parámetros

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green