Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Face Detection with a portable architecture in Real Time

Version 1 : Received: 6 September 2019 / Approved: 9 September 2019 / Online: 9 September 2019 (12:04:50 CEST)

How to cite: De Feo, F.; De Luca, P. Face Detection with a portable architecture in Real Time. Preprints 2019, 2019090100. https://doi.org/10.20944/preprints201909.0100.v1 De Feo, F.; De Luca, P. Face Detection with a portable architecture in Real Time. Preprints 2019, 2019090100. https://doi.org/10.20944/preprints201909.0100.v1

Abstract

Nowadays, security is a top priority. In fact, biometrics uses cutting-edge technologies to identify terrorists and criminals. But the practice of distinguishing humans based on intrinsic physical or behavior traits goes back thousands of years. With the widespread use of computers in the late 20th century, new possibilities for digital biometrics emerged and new technologies were generously used. Among these, we remember high resolution security video cameras and drones. So, the aim of the present project is to study and explain the features of these technologies, especially the ones of the the Phantom 4 Pro+ aircraft and analyze its operating methods in order to identify human faces during live streaming of videos. For this purpose, it will be used Paul Viola and Michael Jones’ face detection algorithm, which includes Haar features and cascade classifiers to identify faces, eyes and ears of an individual.

Keywords

Face detection; Drone; Real Time

Subject

Computer Science and Mathematics, Robotics

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