Facial recognition system
A facial recognition system is a technology that can match a human face from a digital image or a video frame against a database of faces. It works by locating and measuring facial characteristics from a given image and is commonly used to verify users through ID verification services.
Similar systems were first developed in the 1960s as a type of computer application. Facial recognition systems have been used on smartphones and in other types of technology, such as robots, since their beginnings. Computerized facial recognition systems are classified as biometrics since they involve the assessment of a person’s physiological properties.
Governments and commercial organizations use facial recognition technologies all around the world nowadays. Their performance varies, and several methods have been abandoned in the past due to inefficiency. Face recognition systems have also sparked debate, with concerns that they infringe on residents’ privacy, frequently make inaccurate identifications, reinforce gender stereotypes and racial profiling, and fail to preserve crucial biometric data. Face recognition technologies have been banned in various locations across the United States as a result of these allegations. Meta revealed that it aims to shut down Facebook’s facial recognition technology, wiping the face scan data of over one billion users, in response to rising social concerns.
Facial recognition technology’s history
Face recognition software was first developed in the 1960s. Woody Bledsoe, Helen Chan Wolf, and Charles Bisson collaborated on developing a computer that could detect human faces. Because the coordinates of the facial characteristics in an image had to be defined by a person before they could be utilized by the computer for recognition, their early face recognition project was called “man-machine.” A person had to locate the coordinates of face characteristics such as pupil centers, inner and outside corners of eyes, and the widow’s peak in the hairline on a graphics tablet. The coordinates were utilized to compute 20 different distances, including the mouth and eye widths.
Face recognition techniques
Facial identification is a difficult pattern recognition issue in computers, despite the fact that people can recognize faces without much effort. Based on a two-dimensional photograph, facial recognition algorithms try to detect a three-dimensional human face that changes appearance with lighting and facial emotion. Facial recognition systems go through four phases to complete this computational problem. The face is first segmented from the picture backdrop using face detection. The segmented face picture is aligned in the second phase to account for face posture, image size, and photographic qualities like lighting and grayscale. The goal of the alignment method is to allow for precise facial feature localization in the third stage, facial feature extraction.