Since face recognition, by definition, requires face detection, we can think of face recognition as a two-phase process. Face recognition can thus be thought of as a method of person identification, which we use heavily in security and surveillance systems. Unlike face detection, which is the process of simply detecting the presence of a face in an image or video stream, face recognition takes the faces detected from the localization phase and attempts to identify whom the face belongs to. I’ve often seen new computer vision and deep learning practitioners confuse the difference between face detection and face recognition, sometimes (and incorrectly) using the terms interchangeably.įace detection and face recognition are distinctly different algorithms - face detection will tell you where in a given image/frame a face is (but not who the face belongs to) while face recognition actually identifies the detected face. Once we have the face ROI we can perform face recognition, the process of actually identifying who is in the image. First, we must detect the presence of the face using a face detector and extract the face region of interest (ROI). How is face recognition different from face detection?įigure 1: Face recognition can be thought of as a two-step process. These neural networks are capable of obtaining face recognition accuracy that was once thought impossible (and they can achieve this accuracy with surprisingly little data). State-of-the-art face recognition models such as FaceNet and OpenFace rely on a specialized deep neural network architecture called siamese networks. Most recently, we’ve started to utilize deep learning algorithms for face recognition. We simply extract features from the faces, train our classifier, and then use it to identify subsequent faces. ![]() Not only are these systems non-subjective, but they are also automatic - no hand labeling of the face is required. However, these systems were often highly subjective and prone to error since these quantifications of the face were manually extracted by the computer scientists and administrators running the face recognition software.Īs machine learning algorithms became more powerful and the computer vision field matured, face recognition systems started to utilize feature extraction and classification models to identify faces in images. Face recognition is thus a form of person identification.Įarly face recognition systems relied on an early version of facial landmarks extracted from images, such as the relative position and size of the eyes, nose, cheekbone, and jaw. Looking for the source code to this post? Jump Right To The Downloads Section What is face recognition?įace recognition is the process of taking a face in an image and actually identifying who the face belongs to.
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