Visual Programming for Human Detection Using FaceNet in Pocket Code

Abstract

Pocket Code is a visual programming-based mobile application for creating games, animations, music, videos, and other types of applications. This paper presents the integration of face recognition capabilities into Pocket Code through a visual programming interface based on the FaceNet architecture. The FaceNet dataset is used to train and deploy a face recognition model in Pocket Code visual programming. Integration of the FaceNet algorithm into Pocket Code aims to enhance the accessibility and simplicity of facial recognition technology for students and developers. Building face recognition applications typically involves writing complex code, which can be challenging for both beginners and experienced developers. The Pocket Code visual programming blocks have simplified the process, enabling anyone to easily incorporate face detection into their projects, irrespective of their coding experience. The article discusses the implementation and performance assessment of the FaceNet algorithm in Pocket Code visual programming.