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First of all, I am not talking about the utilities that can be used to crop positive images.

I want to know the best way to crop the object of interest so that minimal number of +ve images produce good detection results. There can be two types of objects, 1. Which can be cropped easily with a rectangle including considerable number of object features (objects roughly in rectangular/circular shapes)

1. Whose features cannot be captured easily in rectangle without keeping the background too in the cropping rectangle (objects in shapes like star maybe; like aircraft)

I have attached a sample cropped image of an aircraft. I am trying to build a cascade classifier with similarly cropped images but my training doesn't proceed beyond 4 stages (False detection rate achieved with 4000 +ves, 30000 -ves).

Please suggest:

1. Is it because of my cropping style or something else is wrong, that the learning stops at stage:4

2. I am using images from a single aircraft model at fairly close angles (extracted from a video), but still covering 180 deg view I require for detection. It it required to have +ve images only from same view angle?

3. Please use the attached cropped image and suggest what would be the best cropping style for these type of objects.

Thanks.

First of all, I am not talking about the utilities that can be used to crop positive images.

I want to know the best way to crop the object of interest so that minimal number of +ve images produce good detection results. There can be two types of objects, 1.

1. Which can be cropped easily with a rectangle including considerable number of object features (objects roughly in rectangular/circular shapes)

   2. Whose features cannot be captured easily in rectangle without keeping the background too in the cropping rectangle (objects in shapes like star maybe; like aircraft)

   I have attached a sample cropped image of an aircraft. I am trying to build a cascade classifier with similarly cropped images but my training doesn't proceed beyond 4 stages (False detection rate achieved with 4000 +ves, 30000 -ves).

   Please suggest:

   1. Is it because of my cropping style or something else is wrong, that the learning stops at stage:4

   2. I am using images from a single aircraft model at fairly close angles (extracted from a video), but still covering 180 deg view I require for detection. It it required to have +ve images only from same view angle?

   3. Please use the attached cropped image and suggest what would be the best cropping style for these type of objects.

   Thanks.