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The Viola–Jones algorithm for face detection uses Haar-like features to locate faces in an image. Here a Haar feature that looks similar to the bridge of the nose is applied onto the face. Until the 1990s, facial recognition systems were developed primarily by using photographic portraits of human faces.
Facial recognition works by pinpointing unique dimensions of facial features, which are then rendered as a vector graphic image of the face. Fawkes is a facial image cloaking software created by the SAND (Security, Algorithms, Networking and Data) Laboratory of the University of Chicago . [ 1 ]
Face detection can be used as part of a software implementation of emotional inference. Emotional inference can be used to help people with autism understand the feelings of people around them. [8] AI-assisted emotion detection in faces has gained significant traction in recent years, employing various models to interpret human emotional states.
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PimEyes is a facial recognition search website that allows users to identify all images on the internet of a person given a sample image. The website is owned by EMEARobotics, a corporation based in Dubai.
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DeepFace is a deep learning facial recognition system created by a research group at Facebook.It identifies human faces in digital images. The program employs a nine-layer neural network with over 120 million connection weights and was trained on four million images uploaded by Facebook users.
Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1] Well-researched domains of object detection include face detection and pedestrian detection.
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