Face recognition is the process of identifying one or more people in images or videos by analyzing and comparing patterns. Algorithms for face recognition typically extract facial features and compare them to a database to find the best match. Face recognition is an important part of many biometric, security, and surveillance systems, as well as image and video indexing systems.
Face recognition leverages computer vision to extract discriminative information from facial images, and pattern recognition or machine learning techniques to model the appearance of faces and to classify them.
You can use computer vision techniques to perform feature extraction to encode the discriminative information required for face recognition as a compact feature vector using techniques and algorithms such as:
Machine learning techniques can applied to the extracted features to perform face recognition or classification using:
See also: Statistics and Machine Learning Toolbox, Computer Vision System Toolbox, MATLAB and OpenCV, machine learning, object detection, object recognition, feature extraction, stereo vision, optical flow, RANSAC, pattern recognition, research with MATLAB
Learn how to perform object detection and recognition