Need of Eye detection in Face Recognition?

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There is a difference between detection and actual recognition, one you should clearly make. The detection is done by LBPH and probably the boosted cascade of weak classifiers approach by Viola & Jones, which is in fact the most common used face detector.

Once you have detected the face, recognition can be done in many ways, by using the detected region of interest. Some possible and good techniques are : example based matching, fisherfaces, eigenfaces, ...

The eye detection is needed to allign your face so that the chance of recognition is higher for your region of interest. However, the most recognition algorithms, when trained with enough examples of faces do not need an alignment, since the recognition for each person is trained by using training samples containing several small rotations of the face.

So you could remove this feature to detect and recognize faces if in your application, the faces appear mostly upright.

Someone wearing glasses doesn't affect the detection of the face, since enough other face features can be detected. However, for detecting eye regions, glasses can introduce reflections and distortions which lead to more difficult find of specific eye features. Its also possible that the trained classifier did not have enough glasses wearing examples. If you want better results, the only way is to train your own detector and inner classifier.

So concrete - face detection model - does detect faces with glasses - eye models - do it sometimes, but not exhaustively trained for that purpose, so not best choice to go with here

About the different classifier models, it is actually the game of trial and error. Just try the different models for your application and try to find out which works best for you.

Algorithms used in those applications, if they are recognition, do require you to supply some test data of a person. Else the algorithm doesnt have any data to create a unique identifier for a person. However, when supplied with this data, if the identifier is unique enough, it will indeed not ask for more data during the use. Remember that these techniques however are highly influenced by lighting and other distortions.

Just my 2 cents!

The eye detection by Haar Cascades is not nearly as precise enough as needed for proper image alignment. If you run some tests, you'll soon notice it generates way too many false positive/false negative predictions to be useful in unconstrained scenarios. Contrary to Steven Puttemans remarks, all face recognition algorithms I know of greatly improve with a proper image alignment. This is simply because most of the face recognition algorithms I know of do rely on non rotational-invariant features, hence they can only compensate slight misalignment. I've talked to Tal Hassner, who did research on unconstrained face recognition and here is what he said:

We have found that alignment of faces has a dramatic effect on face recognition performance (see our ACCV and BMVC papers) So much so, that we released our own aligned version of the LFW data set, which alone pushes accuracy up about 8% using existing methods (you can find the set here: http://www.openu.ac.il/home/hassner/data/lfwa/).

That said, head pose estimation and image alignment is a tough problem and it is not solved entirely. I guess you can find commercial solutions, but I can neither recommend one nor comment on their performance. Recent advances in this research area led to very accurate feature detectors (although slow):

• X. Zhu, D. Ramanan. "Face Detection, Pose Estimation and Landmark Localization in the Wild" Computer Vision and Pattern Recognition (CVPR) Providence, Rhode Island, June 2012. (Project page), (PDF Online available), (C++ Source code)

A probably less accurate, but faster approach is given in:

• Gary B. Huang, Vidit Jain, and Erik Learned-Miller. "Unsupervised joint alignment of complex images." International Conference on Computer Vision (ICCV), 2007. (Project page), (PDF Online available), (C++ Source code)

If anyone can add feature detectors or relevant publications to the list, please feel free to post them!