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can you tel me more about how to modifiy the cascade and the training classifier code of opencv, some ideas, ... please

Exactly !!

i have already apply this descriptors in a svm context for classification, now my goal is to apply them in object detection context. To compute these descriptors : - i compute the ffteshift of the input image, then i evaluate this fftshift in a regular hexagonal grid points, for each hexgon 6 points, i get a W(f) vector dim 6x2, finally the combination of theses vectors give the invariant descriptor of the image, and it's a vector dim 1xN. (sorry, i can't share the code of computing these descriptors now, it will be after submitting the paper) I tested my descriptors against coil and orl database for classification, and i got accuracy = 97% good classification. Now the next step is to test them in object detection context. Thanks

my fourier descriptors are computed globaly in the image, i.e, for each image, one vector descriptor is computed, so for a database of 2500 faces , i have 2500 fourier descriptors ( vector size = 1x4417 ). now, i'm blocked at the training classifier step. thanks

I want to use openCV objet detection model with my own features "fourrier descriptors". I know how to do this using the haar features ( the Viola & Jones method ), now i want to use the same processus using my own customised features. Do you have any idea plz? Thanks for your help, Amine.