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Automatic face detection with OpenCV. Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. [1] Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene.
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 .
Structure Core uses a stereo camera that matches against a random pattern of projected infrared points to generate a dense 3D image. Intel RealSense camera projects a series of infrared patterns to obtain the 3D structure. Face ID system works by projecting more than 30,000 infrared dots onto a face and producing a 3D facial map.
Real-time face detection in video footage became possible in 2001 with the Viola–Jones object detection framework for faces. [28] Paul Viola and Michael Jones combined their face detection method with the Haar-like feature approach to object recognition in digital images to launch AdaBoost, the first real-time frontal-view face detector. [29]
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In computer vision, 3D object recognition involves recognizing and determining 3D information, such as the pose, volume, or shape, of user-chosen 3D objects in a photograph or range scan. Typically, an example of the object to be recognized is presented to a vision system in a controlled environment, and then for an arbitrary input such as a ...