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Our task is to make a binary decision: whether it is a photo of a standardized face (frontal, well-lit, etc) or not. Viola–Jones is essentially a boosted feature learning algorithm, trained by running a modified AdaBoost algorithm on Haar feature classifiers to find a sequence of classifiers ,,...,. Haar feature classifiers are crude, but ...
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 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. [3] A reliable face-detection approach based on the genetic algorithm and the eigen-face [4] technique:
Facial recognition algorithms can help in diagnosing some diseases using specific features on the nose, cheeks and other part of the human face. [75] Relying on developed data sets, machine learning has been used to identify genetic abnormalities just based on facial dimensions. [76] FRT has also been used to verify patients before surgery ...
LBPLibrary is a collection of eleven Local Binary Patterns (LBP) algorithms developed for background subtraction problem. The algorithms were implemented in C++ based on OpenCV. A CMake file is provided and the library is compatible with Windows, Linux and Mac OS X. The library was tested successfully with OpenCV 2.4.10.
Feature extraction is performed on raw data prior to applying k-NN algorithm on the transformed data in feature space. An example of a typical computer vision computation pipeline for face recognition using k-NN including feature extraction and dimension reduction pre-processing steps (usually implemented with OpenCV): Haar face detection
The Facial Recognition Technology (FERET) database is a dataset used for facial recognition system evaluation as part of the Face Recognition Technology (FERET) program.It was first established in 1993 under a collaborative effort between Harry Wechsler at George Mason University and Jonathon Phillips at the Army Research Laboratory in Adelphi, Maryland.
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.