Face is one of the most common non-verbal channels through which humans transfer their inner emotional state by face. Face recognition has a great application in various fields such as growth psychology, behavioral science, and human and computer interface. In the new age, authentication is done using various methods, especially fingerprinting and face recognition.
The first experience of face detection was seen in 1960, which referred to the drawing methods. Nobody at that time was managed to imagine that half a century later, face recognition software can be used by police, security experts, government, and even as a password in face time attendance. Now, Microsoft uses face recognition software to authenticate users in Windows 10 while, researchers in Germany are developing a new face recognition technology that it can identify people in the dark.
3D Face Recognition Technology
Computer algorithms, a system for identifying a person by measuring certain features of his face, such as the distance between eyes and the width of the nose, deals with face recognition. Face recognition is moving from the two-dimensional system to the 3D. This help to identify the person better. Additionally, software engineers are likely to easily convert images from two-dimensional to 3D without losing key information or ID.
Much cognitive science research in human face processing claims that identifying faces is much more general than recognizing other objects. That means face recognition is not detected only by identifying and taking into every single feature. As you know, a human's eye blinks simultaneously; the key to starting the face recognition process is blinking eyes and detecting the living tissue of the skin instead of face a mask.
The Importance of Face Recognitiontion Devices
Achieving acceptable accuracy for face recognition and another are two challenges memory and time-consuming. Therefore, there is always a need to provide a new approach to identifying persons in the large data set at an acceptable time and memory. Recognition and identifying face are multidisciplinary research that uses basic computer techniques, image processing, and modeling. Neural networks have been widely developed until tracking issues in the extraction feature, identify a pattern, and generally identify similar problems.
One of the challenges in face recognition that has recently attracted much attention in computer and pattern recognition Face recognition is based on angles and facial gestures relative to the camera. A face recognition system's main goal is to retrieve images similar to a face from the databases. Face images retrieved can be used for many applications such as image surveillance, face recognition, and search of specific faces from the internet.
Today, face recognition technology plays an important role in displaying advertisements for audiences. Using face recognition technology in CCTV cameras, depending on the type of contact that a lady or the sir is after recognizing the audience's face, Ads that fit these types of people can appear in the waiting queue of the hospital or stores.
Now at Miami airport, facial recognition devices are currently being used to save time for people using existing face recognition devices. In addition to matching the person's face with his passport photo, the person's background will simultaneously be checked at the US police database.