I hope that this question is not OT.
I'm implementing a VLAD encoder using the VLFeat implementation and SIFT descriptors from different implementations to compare them (OpenCV, VLFeat, OpenSIFT).
This is supposed to be an high performance application in C++ (I know that SIFT is very inefficient, I'm implementing a parallel version of it).
Now, VLAD wants as input the pointer to a set of contiguous descriptors (math vectors). The point is that usually this SIFT descriptors are represented as a matrix, so it's easier to manage them.
So supposing that we have a matrix of 3 descriptors in 3 dimensions (I'm using these numbers for sake of simplicity, actually it's thousands of descriptors in 128 dimensions):
1 2 3
4 5 6
7 8 9
I need to do feed vl_vlad_encode with the pointer to:
1 2 3 4 5 6 7 8 9
An straightforward solution is saving descriptors in a cv::Mat m object and then pass m.data to vl_vlad_encode.
However I don't know if cv::Mat is an efficient matrix representation. For example, Eigen::Matrix is an alternative (I think it's easy to obtain the representation above using this object), but I don't know which implementation is faster/more efficient or if there is any other reason because I should prefer one instead of the other.
Another possible alternative is using std::vector<std::vector<float>> v, but I don't know if using v.data() I would obtain the representation above instead of:
1 2 3 *something* 4 5 6 *something* 7 8 9
Obviously *something* would mess up vl_vlad_encode.
Any other suggestion is more than welcome!
Unless you do some weird stuff (see here for details), data in a Mat are guaranteed to be continuous. You can think of a Mat as a lightweight wrapper over a float* (or other types) that allows easier access to the data. So it's as efficient as a pointer, but with a few nice-to-have abstractions.
If you need to efficiently load/save from/to file, you can save the Mat in binary format using matread and matwrite.