Face Recognition

Face recognition with computer vision

Face recognition is the process of identifying one or more people in images or videos. 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.

You can recognize faces in MATLAB^® with Computer Vision System Toolbox^™, Statistics Toolbox^™, and Neural Network Toolbox^™ using a variety of models, including:

• Extracted features and boosted learning algorithms
• Principal components analysis models such as Eigenfaces
• Neural network models such as dynamic link matching
• Template matching

Examples and How To

• Face Detection and Tracking (Example)
• Computer Vision with MATLAB (Webinar)
• Pattern Matching (Example)
• Barcode Recognition (Example)
• Abandoned Object Detection (Example)

Software Reference

• Detect Objects Using the Viola-Jones Algorithm (System Objects)
• Object Detection, Motion Estimation, and Tracking (Documentation)
• Feature Detection, Extraction, and Matching (Documentation)

See also: Steve on Image Processing, image and video processing, object recognition, MATLAB and OpenCV, object detection, image recognition