Comparative of viola-jones and YOLO v3 for face detection in real time

Abstract EN

This Face detection is considering one of the important topics for recognizing human, it is the first step before the face recognition process, it is considered one of the biggest challenges in the field of vision computer.

In recent years Many algorithms for detection have appeared, which depend on extracting the features of the human face, and works continue to develop them to this day.

This paper aims to make a comparison between two of the most commonly face detection methods, Viola Jones (V_J) and YOLO v3.

This comparison is made to determine which of the two algorithms is being most useful when used to detect faces in digital video.

These algorithms are used in many applications, including image classification, medical analysis of image, and objects detection in real time (especially in surveillance cameras).

Both algorithms are applied to detect faces in the real time video.

The experimental results of a sample consists of 20 video frames show that V_J algorithm consumes less time in comparison with YOLO v3 algorithm, but its results are less accurate, unlike the YOLO v3 algorithm, which is slower in detect face with high accurate rate.