Face Recognition for classifying digital photos?

Question

I like to mess around with AI and wanted to try my hand at face recognition the first step is to find the faces in the photographs. How is this usually done? Do you use convolution of a sample image/images or statistics based methods? How do you find the bounding box for the face? My goal is to classify the pictures of my kids from all the digital photos.

Thanks in advance.

Answer 1

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

Answer 2

you can try ASM,AAM

http://code.google.com/p/aam-opencv/

or some faceAPI

http://www.seeingmachines.com/product/faceapi/

http://www.luxand.com/facesdk/

http://betaface.com/

Answer 3

OpenCv for C# OpenCvSharp

Sample Code for Face detect

Answer 4

Try this:

OpenCV

This should help you out with face detection and object recognition projects

Answer 5

Have a look at http://www.face-rec.org/algorithms/ - you'll see that there are a variety of ways of going about this.

Assuming you're wanting to code the whole thing yourself, you'll need to look into Bayesian Frameworks, Neural Networks, possibly maths ones like Linear Discriminant Analysis (LDA) and the cool-named Elastic Bunch Graph Matching.

However it's worth noting that there are sooo many people who have coded this around the world, that there are now ready to use, open source, off the shelf apps, apis and libraries that you can simply call. Or neural networks you can plug in - for example - TiNA.

Do a good bit of reading - it's a fascinating topic, and then decide whether you want to go through reinventing the wheel (hey, it's fun to code, but it may not be what you want to focus on) or whether you'll inherit and extend some library or API.

Enjoy!