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Eigenface algorith can be improved!

asked 2014-01-07 03:41:36 -0500

dervish79 gravatar image

updated 2014-01-07 03:44:04 -0500

berak gravatar image

This paper suggests that discarding the three most significant principal components, the variation due to lighting is reduced, then Eigenface gives better output. Q1: does somebody can suggest how to do so, or even are we able to modify the Opencv code to remove three components of PCA ? Another suggestion to be able to update the model incrementally, we can apply an incremental PCA algorithm for this purpose.

Q2: is it possible to do so on OpenCV code?

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worth trying, but won't be easy. you'll have to come up with a special version of this , that ignores the 1st 3 rows.

berak gravatar imageberak ( 2014-01-08 08:00:55 -0500 )edit

Can someone tell me why I get a big distance when calling predict function ?? I initialized the constructor on Test data of the same database (best case) : createEigenFaceRecognizer(30,100); => recognition rate =0 createEigenFaceRecognizer(50,100); => recognition rate =0 createEigenFaceRecognizer(0,100); => recognition rate =0

dervish79 gravatar imagedervish79 ( 2014-01-21 02:53:29 -0500 )edit

When I initialize as: createEigenFaceRecognizer(); => recognition rate = is good, but the distance returned by predict reaches up to 5000 !!!! But some true recognitions are returned by a distance equals to about 4000, where some FALSE recognitions by a distance equals to 1500!!!!!! can some one help me to get a reasonable configuration ??

dervish79 gravatar imagedervish79 ( 2014-01-21 02:59:28 -0500 )edit

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answered 2014-01-08 05:05:06 -0500

vivek0402 gravatar image

By Using OpenCv library you can not do this. You will have to recode the algorithm and while computing P.C.A., neglect first three values. then launch it as revised version of Eigen FaceRecognition Algorithm.

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Asked: 2014-01-07 03:41:36 -0500

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Last updated: Jan 08 '14