TY - JOUR
T1 - Deep-learning-based adaptive advertising with augmented reality
AU - Moreno-Armendáriz, Marco A.
AU - Calvo, Hiram
AU - Duchanoy, Carlos A.
AU - Lara-Cázares, Arturo
AU - Ramos-Diaz, Enrique
AU - Morales-Flores, Víctor L.
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - In this work we describe a system composed of deep neural networks that analyzes characteristics of customers based on their face (age, gender, and personality), as well as the ambient temperature, with the purpose of generating a personalized signal to potential buyers who pass in front of a beverage establishment; faces are automatically detected, displaying a recommendation using deep learning methods. In order to present suitable digital posters for each person, several technologies were used: Augmented reality, estimation of age, gender, and estimation of personality through the Big Five test applied to an image. The accuracy of each one of these deep neural networks is measured separately to ensure an appropriate precision over 80%. The system has been implemented into a portable solution, and is able to generate a recommendation to one or more people at the same time.
AB - In this work we describe a system composed of deep neural networks that analyzes characteristics of customers based on their face (age, gender, and personality), as well as the ambient temperature, with the purpose of generating a personalized signal to potential buyers who pass in front of a beverage establishment; faces are automatically detected, displaying a recommendation using deep learning methods. In order to present suitable digital posters for each person, several technologies were used: Augmented reality, estimation of age, gender, and estimation of personality through the Big Five test applied to an image. The accuracy of each one of these deep neural networks is measured separately to ensure an appropriate precision over 80%. The system has been implemented into a portable solution, and is able to generate a recommendation to one or more people at the same time.
KW - Augmented reality
KW - Computer vision
KW - Deep learning
KW - Emotion-based recommendation
KW - Targeted advertising
UR - http://www.scopus.com/inward/record.url?scp=85121483862&partnerID=8YFLogxK
U2 - 10.3390/s22010063
DO - 10.3390/s22010063
M3 - Artículo
C2 - 35009606
AN - SCOPUS:85121483862
SN - 1424-8220
VL - 22
JO - Sensors
JF - Sensors
IS - 1
M1 - 63
ER -