You don't need to resize or crop your samples but you need to use an annotation tool to create a list of positive samples in the following format:
path_to\sample1.png 1 10 10 20 22
path_to\sample2.png 2 10 10 20 22 40 40 30 33
...
That takes care of all of the issues your were concerned about. Depending on your samples, creating this text file can become time consuming.
Too much background inside the bounding box of your positive samples may affect the effectiveness of the weak classifiers in your model, but it may or may not be important in the final cascade of classifiers model. All you should be concerned about is to create good positive samples where the object is captured inside the bounding box as precisely as possible. It means:
- having each sample in the same relative location to the top-right corner of its corresponding bounding box, and
- having same object width/bounding box width ratio for all samples.
In other words, try centering all objects in your bounding box and add the same "percentage" of padding for all of them so that when they are cropped and resized by createsamples into a vec file, all of them look similar in locations and size.