Frames extracted from video streaming to recognition of face: LBPH, FF and CNN

There are different methods that can be used to uniquely identify one individual from another like Face recognition, Fingerprints, Iris, Signature, etc. Face recognition has gained a lot of popularity due to its wide range of applications in image processing, biometrics. The objective of this project is to detect a human face and identify the person from the set of images from the database when the camera is streaming. A database is created by capturing frames by the camera. The LBPH algorithm, Fisher Face algorithms are used for Face Detection, Feature Extraction and Face Recognition. A Convolutional Neural Network with different layers is constructed, and the model is compiled. The result shows recognized faces when camera is streaming.