Bad efficiency in LBP
i am working on a code that uses face detection first. the detected face is stored and then face recognition, gender and age detection is done on the image. its basically the same code (using LBP), i just train it thrice with three different databases for training. i initially used the at&t face database. eventually i appended a few of my pictures in the database too. now, the real problem is with the efficiency. theoretically LBP promises 96+ % efficiency but i am not even close to that. where could i be going wrong?? please help!! i need to submit the project this week.
preprocessing like equalizeHist, cropping seems to be crucial.
if you get too many false positives, there's a threshold param, that you can set via:
(unfortunately, that won't help you with false negatives)
also, unlike the fisher and eigen methods(which need a LOT of other faces to build an optimal pca ) you won't gain much by throwing more databases at lbp
you say: "eventually i appended a few of my pictures in the database too".
how many per person ? maybe you just did not take enough ? 10-20 seems to be good.
i did append 10 images per new person i added to the database