An Advancement towards Efficient Face Recognition Using Live Video Feed: "For the Future"

Image based or live video feed based face recognition is a very interesting field in research and applications. Various face recognition methods have been devised and applied over the past several years of technological development. Fields like security and surveillance have widely used face recognition over the years as people are very concerned as to identifying and catching criminals or people with mal intentions. Catching them without being able to promptly recognize and their faces has been a major problem. A person's facial features are dynamic and have variable appearances, which makes it a problem to be very accurate and fast in identification of a person. Not only this, security access controls through face recognizers makes it highly difficult for hackers and crackers to use a person's identity or data. The basic objective of this paper hence is to understand several pre-existing face detection and recognition algorithms and then provide a viable solution for live video based facial recognition with better accuracy, higher speed and efficiency so as to help develop a technology such which can help catch criminals promptly and as well as protect people's privacy and identity from hackers. Many facial databases have been considered so as to differentiate them in conditions of changes in poses, illuminations and emotions. Various other conditions to obstruct identification of faces are discussed later.