TY  - JOUR
T1  - Face Recognition Access Control System using Convolutional Neural Networks
AU - Useche M., Paula Catalina AU - Moreno, Robinson Jimeez AU - Arenas, Javier O. Pinzo 
JO  - Research Journal of Applied Sciences
VL  - 13
IS  - 1
SP  - 47
EP  - 53
PY  - 2018
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2018.47.53
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2018.47.53
KW  - KLT Algorithm
KW  -haar classifier
KW  -convolutional neural network
KW  -computer vision
KW  -Face recognition
KW  -point
KW  -specific
AB  - The following study presents the development of a face access control system using convolutional
neural networks where all the faces of a scene are recognized and classified to allow or deny an individual
access according to their facial characteristics. The system allows the access of two specific people after
individually recognizing them for 5 sec in a video sequence and prevents access when the presence of an
outside person, located within the area of vision is detected. The program uses a face detection system by haar
classifiers, a point tracking system by KLT Algorithm (Kanade-Lucas-Tomasi) and a classification technique
by convolutional neural networks where accuracy percentages are reached above 96%.
ER  -