What is face recognition online?
face recognition online, also called facial detection, is an artificial intelligence (AI)-based computer technology used to find and identify human faces in digital images and video. face recognition technology is often used for surveillance and tracking of people in real time. It is used in various fields including security, biometrics, law enforcement, entertainment and social media.
face recognition online uses machine learning (ML) and artificial neural network (ANN) technology, and plays an important role in face tracking, face analysis and facial recognition. In face analysis, face recognition online uses facial expressions to identify which parts of an image or video should be focused on to determine age, gender and emotions. In a facial recognition system, face recognition data is required to generate a faceprint and match it with other stored faceprints.
Facial Recognition Software
The face identifier procedure simply requires any device that has digital photographic technology to generate and obtain the images and data necessary to create and record the biometric facial pattern of the person that needs to be identified.
Unlike other identification solutions such as passwords, verification by email, selfies or images, or fingerprint identification, Biometric facial recognition uses unique mathematical and dynamic patterns works as a face scanner that make this system one of the safest and most effective ones.
The objective of face recognition online is, from the incoming image, to find a series of data of the same face in a set of training images in a database. The great difficulty is ensuring that this process is carried out in real-time, something that is not available to all biometric face recognition online software providers.
The facial recognition process can perform two variants depending on when it is performed:
The one in which, for the first time, a facial recognition system addresses a face to register it and associate it with an identity, in such a way that it is recorded in the system. This process is also known as digital onboarding with facial recognition.
The variant in which the user is authenticated, before being registered. In this process, the incoming data from the camera is crossed with the existing data in the database. If the face matches an already registered identity, the user is granted access to the system with his credentials.
How facial recognition works
Facial recognition is the process of identifying or verifying the identity of a person using their face. It captures, analyzes, and compares patterns based on the person’s facial details.
The face recognition online process is an essential step in detecting and locating human faces in images and videos.
The face capture process transforms analog information (a face) into a set of digital information (data or vectors) based on the person’s facial features.
The face match process verifies if two faces belong to the same person.
Some benefits of face recognition system
Efficient security
Facial recognition is a quick and efficient verification system. It is faster and more convenient compared to other biometric technologies like fingerprints or retina scans. There are also fewer touchpoints in facial recognition compared to entering passwords or PINs. It supports multifactor authentication for additional security verification.
Improved accuracy
Facial recognition is a more accurate way to identify individuals than simply using a mobile number, email address, mailing address, or IP address. For example, most exchange services, from stocks to cryptos, now rely on facial recognition to protect customers and their assets.
Easier integration
Face recognition technology is compatible and integrates easily with most security software. For example, smartphones with front-facing cameras have built-in support for facial recognition algorithms or software code.
Face recognition online in saiwa
Saiwa’s online face recognition service is based on its face recognition algorithms. Users can experiment with two face detectors in two ways:
Recognition using the Dlib face detector.
Recognition using the MTCNN face detector.
The two methods differ in detecting stage. For more details about both saiwa face recognition online algorithms, please refer to here. After detecting faces and face landmarks with the HOG SVM face detector, the faces are rotated, scaled, and sheared so that the face landmarks are close to the frontal model.
Face coding is done after face recognition and fractalization. All reference images of known reference faces and unknown input faces must be encoded similarly.
Finally, an SVM algorithm classifier, previously trained on all reference faces, is used to find the reference face that matches the unknown input.
Uses of face detection
Entertainment
face recognition online is often used in movies, video games and virtual reality. Facial motion capture is used in face recognition online to electronically convert a human’s facial movements into a digital database using cameras and laser scanners. This database can be used to produce realistic computer animation for movies, games or avatars.
Smartphones
Most smartphones use face detection to autofocus cameras for taking pictures and recording videos. Smartphones can also use face detection in place of passcodes. For instance, users of Apple iPhone X and later models can use face detection to unlock their phones.
Security
Face detection is used in security cameras to detect people who enter restricted spaces or to count how many people have entered an area. An additional use is drawing language inferences from visual cues — a form of lip reading. This can help computers determine who is speaking and what they’re saying, which helps with security applications. Furthermore, face detection can be used to determine which parts of an image to blur to ensure privacy, and used by public security cameras to map streets and the people on them in real time.
Emotional inference
Another application for face detection is as part of a software implementation of emotional inference, which can help people with autism understand the feelings of people around them. The program reads the emotions on a human face using advanced image processing.
