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hi,

am trying to use latent SVM trained with person.xml [of PASCAL VOC]. i've tried several images and there are major problems with it:

1. it draws several bounding boxes all over the place although there is only one person in the image - these bbs are mostly outside the person bb - i.e. too many false positives to say it is even detecting anything - might as well randomly draw bounding boxes :(

2. the person is not detected accurately - i.e the bb doesn't cover or covers only part of the person many times - tried with many many images from UCB, PASCAL, INRIA, etc.

3. lastly, it takes forever to simply process one image - i.e in the order of 1-2 MINUTES on a Macbook Pro - anything so slow is totally not usable.

bottomline - it doesn't seem to work - i've checked most documentation/paper/etc. including Felzenschwalb...'s site, but no idea what is wrong with opencv implementation - does anyone know? apparently it is implemented by U. of Nishni - but no doc anywhere or any pointers - very frustrating!!!

thanks if someone responsible can look into it and respond. ps: tried to submit a bug, but ros bug link/form doesn't let me.

hi,

am trying to use latent SVM trained with person.xml [of PASCAL VOC]. i've tried several images and there are major problems with it:

1. it draws several bounding boxes all over the place although there is only one person in the image - these bbs are mostly outside the person bb - i.e. too many false positives to say it is even detecting anything - might as well randomly draw bounding boxes :(

2. the person is not detected accurately - i.e the bb doesn't cover or covers only part of the person many times - tried with many many images from UCB, PASCAL, INRIA, etc.

3. lastly, it takes forever to simply process one image - i.e in the order of 1-2 MINUTES on a Macbook Pro - anything so slow is totally not usable.

bottomline - it doesn't seem to work - i've checked most documentation/paper/etc. including Felzenschwalb...'s site, but no idea what is wrong with opencv implementation - does anyone know? apparently know?

BTW, the paper states somewhere that it should converge [output result] in just 2 or 3 seconds on a standard desktop - so the implementation seems to be way off both in performance, not to mention accuracy - read somewhere it is implemented by U. of Nishni - but no doc anywhere or any pointers - pointers

sorry to sound so negative - spent a few hours on it and is very frustrating!!!

frustrating!!! thanks if someone responsible can look into it and respond. ps: tried to submit a bug, but ros bug link/form doesn't let me.