Diseño de interfaz usando visión artificial para fines de percepción de indicadores de interés para ambientes de enseñanza virtual en la población universitaria

Enderson Ortega Guillina; Oscar Manuel Duque Suarez

doi:10.61799/2216-0388.250

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Design of interface using artificial vision for the purpose of perceiving indicators of interest for virtual teaching environments in the university population

Enderson Ortega Guillina

Universidad de Pamplona

Oscar Manuel Duque Suarez

Universidad de Pamplona

DOI: https://doi.org/10.61799/2216-0388.250

Published

2018-01-01

Issue

Vol. 8 No. 15 (2018)

Section

Articulos

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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Ortega Guillina, E. and Duque Suarez, O.M. 2018. Design of interface using artificial vision for the purpose of perceiving indicators of interest for virtual teaching environments in the university population. Mundo FESC Journal. 8, 15 (Jan. 2018), 31–40. DOI:https://doi.org/10.61799/2216-0388.250.

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https://plu.mx/plum/a/?doi=10.61799/2216-0388.250

Design, artificial vision, perception, indicators of interest

This article describes the design of a perception system through artificial vision for the purpose
of determining indicators of interest for virtual teaching environments, to measure interest or to
ensure that the user is perceiving what is projected through the screen or system interface. The
design criteria were defined based on the characteristics of the face (recognition of emotions) of the
user, after which he programmed the system through tools and libraries such as OpenCV, Python
and Dlib which have a function for the location of the points of the contour of a person’s face, the
values of the thresholds for both the eyes and the mouth of the user are determined and the system
is validated through tests with 10 selected users, pondering the look and gesticulation and times of
distraction and of attention. The results obtained show that the percentage of average attention of the
users was 50.68% and the percentage of distraction 49.32%. The system allows to measure, through
facial recognition, the interest or distraction of a university student in virtual learning environments.
Keywords: Design, artificial vision, perception, indicators of interest

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Keywords:

Design, artificial vision, perception, indicators of interest

Abstract

References