Comment 105 for bug 507511

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In , rohananil (rohan-anil) wrote :

I dont think MACE Filter would be the way to go. The module i am working on is pam-face-authentication is for authentication that is 1 vs 1 matching. For the design - i had to choose between security vs speed (real-time) vs usability. So adapting it for recognition is out of question. So I dont think its fair to compare it for use in recognition :). And question about face detection - its an implementation available on OpenCV based on a method by Viola and Jones. If you want the performance numbers - http://www.lienhart.de/. He has a paper on it. Also again pam-face-authentication is for realtime authentication - So you have to provide your frontal face to the webcam! :) . I have bigger plans for the authentication system once i perfect my AAM implementation http://code.google.com/p/aam-opencv/, Currently the issue is some manual supervision is required which is a NO-GO with a normal user. It just has to work out of the box. Although the results from AAM-Tracking to Recognition is just phenomenal.

Now coming to the task at hand. We are looking at the topic of unconstrained face recognition. Best - research for our photo tagging - could be to implement the best performing algorithm from http://vis-www.cs.umass.edu/lfw/ results. We could go with a support vector machine implementation with highly efficient features. But bottle-neck is the time required for training. Can we compromise over training time ? The more pictures you have more training time. Now we should pickup an algorithm which does not require retraining over the entire set for new images. I think i can code this over this/next weekend. But need help with integrating with the code base. If anyone could provide me an api spec of how the class should be like I would like a go at it..

regards
Rohan