OpenCV/EmguCV face recognition

I am trying to make an app that detect faces and recognizes it. I made Face detection but I want some idea to when making recognition. I'm using a web cam for tracking and it can detect the face.Then I am taking only the part of the face to a new gray image and comparing it using EigenObjectRecognizer with list of images in database.

But it is not giving good results. Some times it find some thing wrong, some times nothing. I want to ask that for comparing photos which additional techniques I must implement? 开发者_如何转开发Like Histogram equalization or resolution of faces equalization?

I have an OpenCV Face Recognition (Haar Face Detection + Histogram Equalization + Eigenfaces) tutorial and free source code that you could try: http://www.shervinemami.info/faceRecognition.html

Face detection and face classification are completely different problems. I can tell you from my experience and from reading several papers on face classification, that a good way to start is by reading about Principal Component Analysis (PCA also known as Eigenfaces), Fisher's Linear Discriminant Analysis (LDA), and Support Vector Machines (SVMs). These are classification methods that are extremely useful for face classification, and it turns out that OpenCV already includes excellent implementations on PCA and SVM. An excellent resource for face recognition and classification code for OpenCV in C++ is this website.

One website that offers resources and links to papers for most relevant methods for face classification is this one.

A well explained example of PCA Eigenfaces and LDA with sample code in Matlab that was extremely useful for my first face classification program is here.

Eigenfaces will only get you so much further in face recognition. There's a limit with the number of faces you can train. You'll have to look into newer algorithms , check out new papers in this field and implement them.

You can implement the efficiency of Eigenfaces by making sure that all your images are of the same orientation and size. Orientation and position matters a lot. So make sure you apply right transformations before comparison

Check my answer at the link below. There are some links in it that will be helpful to you, mainly the YouTube video I mentioned.

Dice face value recognition