What are the applications of face recognition?
Face recognition is also useful in human computer interaction, virtual reality, database recovery, multimedia, computer entertainment, information security e.g. operating system, medical records, online banking., Biometric e.g. Personal Identification – Passports, driver licenses , Automated identity verification – …
What is OpenIMAJ?
Open Intelligent Multimedia Analysis for Java (OpenIMAJ) OpenIMAJ is an award-winning set of libraries and tools for multimedia content analysis and content generation. and advanced data clustering, through to software that performs analysis on the content, layout and structure of webpages.
Which technology is used for face detection?
Facial recognition is a way of recognizing a human face through technology. A facial recognition system uses biometrics to map facial features from a photograph or video. It compares the information with a database of known faces to find a match.
Which technique is best for face recognition?
What are the steps involved in face detection?
Face recognition is often described as a process that first involves four steps; they are: face detection, face alignment, feature extraction, and finally face recognition.
How is face detection done?
Face detection algorithms typically start by searching for human eyes — one of the easiest features to detect. The algorithm might then attempt to detect eyebrows, the mouth, nose, nostrils and the iris. The methods used in face detection can be knowledge-based, feature-based, template matching or appearance-based.
What is Mtcnn face detection?
MTCNN or Multi-Task Cascaded Convolutional Neural Networks is a neural network which detects faces and facial landmarks on images. It was published in 2016 by Zhang et al. MTCNN is one of the most popular and most accurate face detection tools today. It consists of 3 neural networks connected in a cascade.