BiometricsBiometrics are body measurements and calculations related to human characteristics. Biometric authentication (or realistic authentication) is used in computer science as a form of identification and access control. It is also used to identify individuals in groups that are under surveillance. Biometric identifiers are the distinctive, measurable characteristics used to label and describe individuals. Biometric identifiers are often categorized as physiological characteristics which are related to the shape of the body.
AuthenticatorAn authenticator is a means used to confirm a user's identity, that is, to perform digital authentication. A person authenticates to a computer system or application by demonstrating that he or she has possession and control of an authenticator. In the simplest case, the authenticator is a common password. Using the terminology of the NIST Digital Identity Guidelines, the party to be authenticated is called the claimant while the party verifying the identity of the claimant is called the verifier.
Multivariate kernel density estimationKernel density estimation is a nonparametric technique for density estimation i.e., estimation of probability density functions, which is one of the fundamental questions in statistics. It can be viewed as a generalisation of histogram density estimation with improved statistical properties. Apart from histograms, other types of density estimators include parametric, spline, wavelet and Fourier series. Kernel density estimators were first introduced in the scientific literature for univariate data in the 1950s and 1960s and subsequently have been widely adopted.
Digital identityDigital identity refers to the information utilized by computer systems to represent external entities, including a person, organization, application, or device. When used to describe an individual, it encompasses a person's compiled information and plays a crucial role in automating access to computer-based services, verifying identity online, and enabling computers to mediate relationships between entities. Digital identity for individuals is an aspect of a person's social identity and can also be referred to as online identity.
Identity managementIdentity management (IdM), also known as identity and access management (IAM or IdAM), is a framework of policies and technologies to ensure that the right users (that are part of the ecosystem connected to or within an enterprise) have the appropriate access to technology resources. IdM systems fall under the overarching umbrellas of IT security and data management. Identity and access management systems not only identify, authenticate, and control access for individuals who will be utilizing IT resources but also the hardware and applications employees need to access.
ProsopagnosiaProsopagnosia (from Greek prósōpon, meaning "face", and agnōsía, meaning "non-knowledge"), also known as face blindness, is a cognitive disorder of face perception in which the ability to recognize familiar faces, including one's own face (self-recognition), is impaired, while other aspects of visual processing (e.g., object discrimination) and intellectual functioning (e.g., decision-making) remain intact. The term originally referred to a condition following acute brain damage (acquired prosopagnosia), but a congenital or developmental form of the disorder also exists, with a prevalence of 2.
Emotion recognitionEmotion recognition is the process of identifying human emotion. People vary widely in their accuracy at recognizing the emotions of others. Use of technology to help people with emotion recognition is a relatively nascent research area. Generally, the technology works best if it uses multiple modalities in context. To date, the most work has been conducted on automating the recognition of facial expressions from video, spoken expressions from audio, written expressions from text, and physiology as measured by wearables.
Pattern recognitionPattern recognition is the automated recognition of patterns and regularities in data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess (PR) capabilities but their primary function is to distinguish and create emergent pattern. PR has applications in statistical data analysis, signal processing, , information retrieval, bioinformatics, data compression, computer graphics and machine learning.
