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I am testing some object detection with SURF and SIFT.
SURF claims to be faster and more robust than SIFT but I found in my test that this is not true. SIFT with medium images (600*400) is the same speed of SURF and it recognizes objects pretty well (maybe even better than SURF).
Am I doing something wrong?
[Edit]
Please note there is an article explaining how SURF could be much faster with a little change to opencv code.
If you know some active opencv developer please let him see it.
When it was designed it was intended to be faster, but actually, the differences are not relevant for real-time applications with standard cameras. By the way, FAST detector is faster and quite robust.
I am programming for real-time augmented reality on phones, and we use a combination of SIFT (initialization) and FAST (pyramidal FAST for real-time feature detection) during the application execution. FAST is faster, and it is implemented in OpenCV, so if you don’t want to stick to SURF give it a try. I haven’t seen recent papers that use SURF for real-time but I have seen modified versions of SIFT, with fewer pixels for descriptors and other kinds of modifications, so it seems like SURF was kind of a great idea that didn’t get as far as it was thought to. That is just my opinion, anyway.