Author : Laxmi Narayan Soni and Dr. Akhilesh A Waoo

In this work, we are focusing on the review of the field of face detection where the attention of the researchers has been very less. A lot of work has been done in face detection and face recognition, and many methods were used, but still, the facial recognition of infants, old age people and people with dark skin show this lack of research. This review paper will focus on all those who worked on face detection technology keeping in mind the right to equality and getting better results. The most popular algorithm and methodology for face detection is the Viola-Jones algorithm for many years. This algorithm is based on a combination of Haar-like features and AdaBoost learning. It is widely used in many applications such as facial recognition, security systems, and video surveillance. This paper provides a comprehensive and comparative overview of different methodologies of face detection and the current state-of-the-art in deep learning-based face recognition systems. We found the best AI method for face detection is Convolutional Neural Networks (CNNs). CNNs are a type of deep learning algorithm that can detect and classify objects in images. They are particularly well-suited for face detection because they can learn to recognize patterns in data that are not explicitly labelled.

Keywords: Face Detection, Face recognition, Viola-jones, PCA, ANN, AlexNet, VGGNet, CNN, Deep learning.