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Face Recognition with OpenCV — OpenCV 2.4.7.0 documentation


OpenCV (Open Source Computer Vision) is a popular computer vision library started by Intel in 1999. The cross-platform library sets its focus on real-time image processing and includes patent-free implementations of the latest computer vision algorithms. In 2008 Willow Garage took over support and OpenCV 2.3.1 now comes with a programming interface to C, C++, Python and Android. OpenCV is released under a BSD license so it is used in academic projects and commercial products alike.

OpenCV 2.4 now comes with the very new FaceRecognizer class for face recognition, so you can start experimenting with face recognition right away. This document is the guide I’ve wished for, when I was working myself into face recognition. It shows you how to perform face recognition with FaceRecognizer in OpenCV (with full source code listings) and gives you an introduction into the algorithms behind. I’ll also show how to create the visualizations you can find in many publications, because a lot of people asked for.

The currently available algorithms are:

Eigenfaces (see createEigenFaceRecognizer())
Fisherfaces (see createFisherFaceRecognizer())
Local Binary Patterns Histograms (see createLBPHFaceRecognizer())