The usage of machine learning technology in numerous situations helps to avoid straightforward crimes or even find the offenders in real-time. The way we look sets humans apart from many other species and is a distinctive feature. However, its function extends beyond simple classification; it is also crucial in ascertaining whether an individual belongs to the same species as humans. There is currently a prevalent issue with this significant functionality. Because of the low resolution, the camera is unable to distinguish and identify a person's face when taking an image. However, because of the camera's poor image quality, it can be challenging to identify an incident that takes place after a security camera is placed. However, all that is needed to make it work and identify faces is a strong algorithm; hardware will not be as expensive, nor will it be as involved in that field. Facial recognition can be used to accurately control widgets and apps that rely on it. Facial recognition, an AI-based computing technology, helps locate and identify human faces in digital images and videos. Faces are one of the most important biometrics for identifying individuals in real-time for information processing. Various methods have been proposed to extract and recognize facial features, but they remain challenges for real-time applications. Even with the temporal backdrop, issues and further limits are brought about by factors like occlusion, face identification, and recognition. The purpose of this article is to discuss various face object detection and face recognition algorithms.