Sistema de reconocimiento facial para control de accesos en Autoridad Portuaria de Manta

Abstract

Abstract:The present degree work considered the need of a face recognition access control systemat Autoridad Portuaria de Manta. Asa port,it must have the highest safety standards. Different algorithms of face recognition were researched, from which FaceNet was chosen. It is based on Deep learningand was developed by Google researchers for its speed to train recognition modelsand for its high precision for recognizing faces. During the development of the system, the framework Django inPythonwas implemented,and open libraries specialized in computer vision such as OpenCV were used. The system canrecognize a person s face by capturing a photo from the web browser and then recordthe entry and exit from the premises to track employee attendance.