Add WindowFeature::isCUDA()

This method will be called when running apply on ImageWindowIterator
Playing with CUDA objects, it is better to send the image as a whole to WindowFeature::apply and not just chunks as it was implemented for native-C code.
Rename isCUDA into isApplyOnImage

WindowFeature::isCUDA has been renamed into WindowFeature::isApplyOnImage

By default calling ImageWindowIterator::apply runs WindowFeature::apply on chunks.
Due to lack of performances when dealing with CUDA code, a WindowFeature::apply on image has to be designed.
Rename WindowFeature::apply into WindowFeature::applyOnChunk
Add new WindowFeature methods to cppimagewindowiterator.pyx
ImageWindowIterator chooses between applyOnChunk and applyOnImage
Input image copied to GPU only once for DalalTriggs
Remove unnecessary comment
CUDA version of histogram (d_h) allocated and released only once
Histogram computation done with the whole image
Use already computed factors to compute new ones
Define h as a double* instead of double[]

int* a1 = new int[SIZE];  // SIZE limited only by OS/Hardware
int a2[SIZE]; // SIZE limited by COMPILER to the size of the stack frame
Merge branch 'hog_bug' into cuda_hog_apply_revisited
Apply changes of 'hog_bug' to HOG.cu
<vector>block allocated only once
BUG fixed: Bad check in histogram pre-computation
BUG fixed: Reduce the number of copies for d_h when vect is too large
Remove 'reduce for histograms' step

This choice has been made for performances purpose.
The reduce algorithm was proved less efficient than an atomicAdd version in one kernel, mainly due to non-concealed accesses to histograms memory.

Some experiments on 'reduce version' will maybe find a way to have a significant decrease in runtime using reduce kernel.
Add define statements for time measurements using CUDA
Merge branch 'cuda_fix_compile' into cuda_hog
Merge branch 'cuda_hog' into cuda_hog_fullcuda

Conflicts:
	menpo/image/feature/cu/HOG.cu