Facial Detection
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Facial Detection
Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene. Definition and related algorithms Face detection can be regarded as a specific case of object-class detection. In object-class detection, the task is to find the locations and sizes of all objects in an image that belong to a given class. Examples include upper torsos, pedestrians, and cars. Face detection simply answers two question, 1. are there any human faces in the collected images or video? 2. where is the located? Face-detection algorithms focus on the detection of frontal human faces. It is analogous to image detection in which the image of a person is matched bit by bit. Image matches with the image stores in database. Any facial feature changes in the database will invalidate the matching process. A reliable face-detection ...
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Face Detection
Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene. Definition and related algorithms Face detection can be regarded as a specific case of object-class detection. In object-class detection, the task is to find the locations and sizes of all objects in an image that belong to a given class. Examples include upper torsos, pedestrians, and cars. Face detection simply answers two question, 1. are there any human faces in the collected images or video? 2. where is the located? Face-detection algorithms focus on the detection of frontal human faces. It is analogous to image detection in which the image of a person is matched bit by bit. Image matches with the image stores in database. Any facial feature changes in the database will invalidate the matching process. A reliable face-detection ...
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Face ID
Face ID is a facial recognition system designed and developed by Apple Inc. for the iPhone and iPad Pro. The system allows biometric authentication for unlocking a device, making payments, accessing sensitive data, providing detailed facial expression tracking for Animoji, as well as six degrees of freedom (6DOF) head-tracking, eye-tracking, and other features. Initially released in November 2017 with the iPhone X, it has since been updated and introduced to several new iPhone models, and all iPad Pro models. The Face ID hardware consists of a sensor with three modules; a dot projector that projects a grid of small infrared dots onto a user's face, a module called the flood illuminator that shines infrared light at the face, and an infrared camera which takes an infrared picture of the user, reads the resulting pattern and generates a 3D facial map. This map is compared with the registered face using a secure subsystem, and the user is authenticated if the two faces match suffic ...
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Face Recognition
A facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces. Such a system is typically employed to authenticate users through ID verification services, and works by pinpointing and measuring facial features from a given image. Development began on similar systems in the 1960s, beginning as a form of computer application. Since their inception, facial recognition systems have seen wider uses in recent times on smartphones and in other forms of technology, such as robotics. Because computerized facial recognition involves the measurement of a human's physiological characteristics, facial recognition systems are categorized as biometrics. Although the accuracy of facial recognition systems as a biometric technology is lower than iris recognition and fingerprint recognition, it is widely adopted due to its contactless process. Facial recognition systems have been deployed in advanced human–compu ...
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Human Sensing
Human sensing (also called human detection or human presence detection) encompasses a range of technologies for detecting the presence of a human body in an area of space, typically without the intentional participation of the detected person. Common applications include search and rescue, surveillance, and customer analytics (for example, people counters). Modern technologies proposed or deployed for human sensing include: * Acoustic sensors * Image recognition of human shapes * Infrared detectors * Pressure-sensitive floor tiles * Radar * Chemical sensors * Detection of the mobile phone, computer, Bluetooth, or Wi-Fi signals of a device assumed to be in the possession of a person. *WiFi Sensing Examples In 1997 CAPTCHA ("Completely Automated Public Turing test to tell Computers and Humans Apart") was invented. Test is used for detection that computer is operated by human operator, preventing accessing protected resource by programs , spam robots. Various commercial hear ...
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Visage SDK
Visage may refer to: *A synonym of face * Visage Mobile, an American software as a service company * Visage, Georgia, a community in the United States * ''Visage'' (film), also known as ''Face'', a 2009 French film * ''Visage'' (video game), a survival horror game by SadSquare Studio. *"Visage", a 2003 episode of ''Smallville'' * Venus In Situ Atmospheric and Geochemical Explorer (VISAGE), a 2017 Venus lander proposal by NASA Music *"Visage", a 1961 electro-acoustic work by Luciano Berio *Visage (band), a British pop group ** ''Visage'' (Visage album), a 1980 album by Visage ** "Visage" (song), a 1981 song by Visage ** ''Visage'' (EP), a 1981 compilation EP by Visage ** ''Visage'' (video), a 1986 compilation video by Visage * ''Visage'' (Rob Brown album), a 2000 album by jazz saxophonist Rob Brown *"Visage", a 1968 song by Nicoletta (singer) People with the surname *Bertrand Visage, French writer *Michelle Visage Michelle Lynn Case (nee Shupack), better known as Michelle Vis ...
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TSL Color Space
TSL color space (Tint, Saturation and Lightness ) is a perceptual color space which defines color as tint (the degree to which a stimulus can be described as similar to or different from another stimuli that are described as red, green, blue, yellow, and white, can be thought of as hue with white added), saturation (the colorfulness of a stimulus relative to its own brightness), and lightness (the brightness of a stimulus relative to a stimulus that appears white in similar viewing conditions). Proposed by Jean-Christophe Terrillon and Shigeru Akamatsu, TSL color space was developed primarily for the purpose of face detection. Conversion between RGB and TSL The conversion from gamma-corrected RGB values to TSL is straightforward: T = \begin \frac \arctan + \frac, & \mbox~g'>0 \\ \frac \arctan + \frac, & \mbox~g'\frac \\ \sqrt \cdot S, & \mbox~T<\frac \\ 0, & \mbox~T=0 \\ \end k = \frac x = - \cot () For ...
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Three-dimensional Face Recognition
Three-dimensional face recognition (3D face recognition) is a modality of facial recognition methods in which the three-dimensional geometry of the human face is used. It has been shown that 3D face recognition methods can achieve significantly higher accuracy than their 2D counterparts, rivaling fingerprint recognition. 3D face recognition has the potential to achieve better accuracy than its 2D counterpart by measuring geometry of rigid features on the face. This avoids such pitfalls of 2D face recognition algorithms as change in lighting, different facial expressions, make-up and head orientation. Another approach is to use the 3D model to improve accuracy of traditional image based recognition by transforming the head into a known view. Additionally, most 3D scanners acquire both a 3D mesh and the corresponding texture. This allows combining the output of pure 3D matchers with the more traditional 2D face recognition algorithms, thus yielding better performance (as shown iFRVT ...
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Super Recogniser
"Super recogniser" is a term coined in 2009 by Harvard and University College London researchers for people with significantly better-than-average face recognition ability. Super recognisers are able to memorise and recall thousands of faces, often having seen them only once. Skill It is the extreme opposite of prosopagnosia. It is estimated that 1 to 2% of the population are super recognisers who can remember 80% of faces they have seen compared to 20% of the general population, but these figures are disputed. Super recognizers can match faces better than computer recognition systems in some circumstances. The science behind this is poorly understood but may be related to the fusiform face area part of the brain. Practical applications The skill is recognised and employed among the British intelligence community. In May 2015, the London Metropolitan Police officially formed a team made up of people with this heightened capability for recognising people and put them to work iden ...
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Picasa
Picasa was a cross-platform image organizer and image viewer for organizing and editing digital photos, integrated with a now defunct photo-sharing website, originally created by a company named Lifescape (which at that time was incubated by Idealab) in 2002."Google Picasa", Obsessable (obsessable.com), 2009. "Picasa" is a blend of the name of Spanish painter Pablo Picasso, the phrase ''mi casa'' (Spanish for "my house") and "pic" for pictures. Native applications for Windows XP, Windows Vista, Windows 7, and macOS were available, and for Linux, the Windows version was bundled with Wine compatibility layer. An iPhoto plugin and a standalone program for uploading photos were available for Mac OS X 10.4 and later. In July 2004, Google acquired Picasa from Lifescape and began offering it as freeware. On February 12, 2016, Google announced it was discontinuing support for Picasa Desktop and Picasa Web Albums, effective March 15, 2016, and focusing on the cloud-based Google Photos a ...
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Computer Vision
Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do. Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images (the input of the retina) into descriptions of the world that make sense to thought processes and can elicit appropriate action. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory. The scientific discipline of computer vision is concerned with the theory ...
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