Face Joy Apk

Make sure that nothing is covering the TrueDepth camera or your face. If something is obstructing your nose or mouth, like glasses or a face mask, you might be asked to temporarily remove these items during setup.

On iPad or iPhone 12 or later, you can hold your device in either portrait or landscape orientation. If it's in landscape orientation, make sure that your finger isn't covering the TrueDepth camera. Then glance at the screen. If you're wearing a face mask that covers your mouth and nose, you'll be asked to enter your passcode after swiping up.

Face Joy Apk

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Transcript:\n\nMany parts of the body can be used as verbs in either a physical or a metaphorical sense. You can head a company, but if things go wrong you'll have to shoulder the blame, or face your investors. A good leader backs their employees, but if you don't toe the line you might get skinned. Did you muscle your way into that job? You might eye someone suspiciously, or wait for the police to finger a suspect. But if you need to get out of town, try thumbing a ride. You can ride with me if you can stomach the thought. I don't always sing along to the radio, but you might see me mouthing the words.","fb_legacy_url":null,"is_editor_choice":1,"is_archived":0,"is_published":1,"published_at":"2019-02-26 13:19:00","last_published_at":"2019-02-26 13:19:00","created_at":"2019-02-25 13:19:37","updated_at":"2022-05-17 16:03:21","tldr":null,"jw_id":"1QQElJRD","promo_date":"2024-01-01","promo_type":"Sidekick","promo_index":5,"promo_bucket":"random","promo_category_type":"None","promo_category_index":0}; Dictionary Entries Near face facade

The face is the front of an animal's head that features the eyes, nose and mouth, and through which animals express many of their emotions.[1][2] The face is crucial for human identity, and damage such as scarring or developmental deformities may affect the psyche adversely.[1]

The face is itself a highly sensitive region of the human body and its expression may change when the brain is stimulated by any of the many human senses, such as touch, temperature, smell, taste, hearing, movement, hunger, or visual stimuli.[4]

The face is the feature which best distinguishes a person. Specialized regions of the human brain, such as the fusiform face area (FFA), enable facial recognition; when these are damaged, it may be impossible to recognize faces even of intimate family members. The pattern of specific organs, such as the eyes, or of parts of them, is used in biometric identification to uniquely identify individuals.

The shape of the face is influenced by the bone-structure of the skull, and each face is unique through the anatomical variation present in the bones of the viscerocranium (and neurocranium).[1] The bones involved in shaping the face are mainly the maxilla, mandible, nasal bone and zygomatic bone. Also important are various soft tissues, such as fat, hair and skin (of which color may vary).[1]

The face changes over time, and features common in children or babies, such as prominent buccal fat-pads disappear over time, their role in the infant being to stabilize the cheeks during suckling.While the buccal fat-pads often diminish in size, the prominence of bones increase with age as they grow and develop.[1]

Faces are essential to expressing emotion, consciously or unconsciously. A frown denotes disapproval; a smile usually means someone is pleased. Being able to read emotion in another's face is "the fundamental basis for empathy and the ability to interpret a person's reactions and predict the probability of ensuing behaviors". One study used the Multimodal Emotion Recognition Test[27] to attempt to determine how to measure emotion. This research aimed at using a measuring device to accomplish what many people do every day: read emotion in a face.[28]

Gestalt psychologists theorize that a face is not merely a set of facial features, but is rather something meaningful in its form. This is consistent with the Gestalt theory that an image is seen in its entirety, not by its individual parts. According to Gary L. Allen, people adapted to respond more to faces during evolution as the natural result of being a social species. Allen suggests that the purpose of recognizing faces has its roots in the "parent-infant attraction, a quick and low-effort means by which parents and infants form an internal representation of each other, reducing the likelihood that the parent will abandon his or her offspring because of recognition failure".[31] Allen's work takes a psychological perspective that combines evolutionary theories with Gestalt psychology.

Research has indicated that certain areas of the brain respond particularly well to faces. The fusiform face area, within the fusiform gyrus, is activated by faces, and it is activated differently for shy and social people. A study confirmed that "when viewing images of strangers, shy adults exhibited significantly less activation in the fusiform gyri than did social adults".[32] Furthermore, particular areas respond more to a face that is considered attractive, as seen in another study: "Facial beauty evokes a widely distributed neural network involving perceptual, decision-making and reward circuits. In those experiments, the perceptual response across FFA and LOC remained present even when subjects were not attending explicitly to facial beauty".[33]

Cosmetic surgery can be used to alter the appearance of the facial features.[34] Maxillofacial surgery may also be used in cases of facial trauma, injury to the face and skin diseases. Severely disfigured individuals have recently received full face transplants and partial transplants of skin and muscle tissue.[35]

By extension, anything which is the forward or world-facing part of a system which has internal structure is considered its "face", like the faade of a building. For example, a public relations or press officer might be called the "face" of the organization he or she represents. "Face" is also used metaphorically in a sociological context to refer to reputation or standing in society, particularly Chinese society,[37] and is spoken of as a resource which can be won or lost. Because of the association with individuality, the anonymous person is sometimes referred to as "faceless".

NIST has published NISTIR 8331 - Ongoing FRVT Part 6B: Face recognition accuracy with face masks using post-COVID-19 algorithms on November 30, 2020, the second out of a series of reports aimed at quantifying face recognition accuracy for people wearing masks. This report adds 1) 65 new algorithms submitted to FRVT 1:1 since mid-March 2020 (and includes cumulative results for 152 algorithms evaluated to date) and 2) assessment of when both the enrollment and verification images are masked (in addition to when only the verification image is masked). Our initial approach has been to apply masks to faces digitally (i.e., using software to apply a synthetic mask). This allowed us to leverage large datasets that we already have. This report quantifies the effect of masks on both false negative and false positives match rates. For more information, visit the FRVT Face Mask Effects webpage.

NIST describes and quantifies demographic differentials for contemporary face recognition algorithms in this report, NISTIR 8280. NIST has conducted tests to quantify demographic differences for nearly 200 face recognition algorithms from nearly 100 developers, using four collections of photographs with more than 18 million images of more than 8 million people.

The FRVT Ongoing activity is conducted on a continuing basis and will remain open indefinitely such that developers may submit their algorithms to NIST whenever they are ready. This approach more closely aligns evaluation with development schedules. The evaluation will use very large sets of facial imagery to measure the performance of face recognition algorithms developed in commercial and academic communities worldwide. Multiple evaluation tracks relevant to face recognition will be conducted under this test. For more information, visit the FRVT Ongoing webpage.

The FRVT 1:N 2018 will measure advancements in the accuracy and speed of one-to-many face recognition identification algorithms searching enrolled galleries containing at least 10 million identities. The evaluation will primarily use standardized portrait images, and will quantify how accuracy depends on subject-specific demographics and image-specific quality factors. For more information, visit the FRVT 1:N 2018 webpage.

Facial morphing and the ability to detect it is an area of high interest to a number of photo-credential issuance agencies and those employing face recognition for identity verification. The FRVT MORPH test will provide ongoing independent testing of prototype facial morph detection technologies.

NIST is establishing an evaluation of face image quality assessment algorithms. NIST will run quality assessment algorithms on large sets of images and relate their outputs to face recognition outcomes.

While not part of the FRVT series, the Face-in-Video-Evaluation (FIVE) conducted 2015-2016 will be of interest to the FRVT audience. The FIVE activity assessed face recognition capability in video sequences. The outcomes of FIVE were published in NIST Interagency Report 8173.

The Face Recognition Algorithm Independent Evaluation (CHEXIA-FACE) was conducted to assess the capability of face detection and recognition algorithms to correctly detect and recognize children's faces appearing in unconstrained imagery.

FRVT 2013 tested state-of-the-art face recognition performance. It used very large sets of facial imagery to measure the accuracy and computational efficiency of face recognition algorithms developed in commercial and academic communities worldwide. The test itself ran from July 2012 to the end of 2013. The detailed plans, procedures and outcomes of the test are documented on the FRVT 2013 homepage.

Under the name MBE 2010, 2D face recognition algorithms were evaluated, yielding two reports. First, NIST Interagency Report 7709 gave results for both verification and identification algorithms. Second, the NIST Interagency Report 7830 surveyed compression and resolution parameters for storing face images on identity credentials. 9af72c28ce