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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 .
For a discussion on the vulnerabilities of Facenet-based face recognition algorithms in applications to the Deepfake videos: Pavel Korshunov; Sébastien Marcel (2022). "The Threat of Deepfakes to Computer and Human Visions" in: Handbook of Digital Face Manipulation and Detection From DeepFakes to Morphing Attacks (PDF). Springer. pp. 97–114.
It is widely used in computer vision tasks such as image annotation, [2] vehicle counting, [3] activity recognition, [4] face detection, face recognition, video object co-segmentation. It is also used in tracking objects, for example tracking a ball during a football match, tracking movement of a cricket bat, or tracking a person in a video.
Facial recognition software at a US airport Automatic ticket gate with face recognition system in Osaka Metro Morinomiya Station. A facial recognition system [1] is a technology potentially capable of matching a human face from a digital image or a video frame against a database of faces.
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 face 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 ...
Video, sound files Classification, face recognition, voice recognition 2018 [82] [83] S.R. Livingstone and F.A. Russo SCFace Color images of faces at various angles. Location of facial features extracted. Coordinates of features given. 4,160 Images, text Classification, face recognition 2011 [84] [85] M. Grgic et al. Yale Face Database
The position of these rectangles is defined relative to a detection window that acts like a bounding box to the target object (the face in this case). In the detection phase of the Viola–Jones object detection framework , a window of the target size is moved over the input image, and for each subsection of the image the Haar-like feature is ...
The algorithms for solving this problem are specialized for locating a single pre-identified object, and can be contrasted with algorithms which operate on general classes of objects, such as face recognition systems or 3D generic object recognition. Due to the low cost and ease of acquiring photographs, a significant amount of research has ...