Hugo Teixeira's profile - activity

I think the problem is the memory allocation during the extractor.compute(img_mat, keypoints1, descriptors1) function. If I call it twice, the second time is much faster, even if I change the img_mat to a completely different image. Now I achieve speed of ~200ms with FAST and less than 10ms with ORB and STAR

Actually I don't think it's possible if you are using OpenCV 2.4.3. The nonfree module is not included in this version. For Android I think the last one to have SURF and SIFT was 2.4.0. You can use this version but then you can't use OpenCV Manager

Depends on the image but FAST always gives me more than 1000, ORB between 430 and 460 and STAR less than 100. FAST detection takes between 25 and 35 ms, ORB 90-115 ms and STAR 115-120 ms

But the execution time I measure concerns only the extracting. Keypoint detection execution time is very fast in all three I used

Hey. I've tried detection with FAST, ORB and STAR. In all of them it takes over 6s

Hello,

I'm developing an Android app that requires object recognition. I built a PC desktop version where I use FREAK as a descriptor extractor and it provided very satisfying results. However, in my Android app, FREAK is incredibly slow. No matter which feature detector I use FREAK requires at least 6 seconds to extract. I find this very weird since ORB requires less than 1 second (also as a descriptor extractor) and BRIEF requires even less. Even SIFT and SURF as extractors are faster. I've seen topics here where people commented that FREAK speed was not as good as expected but nobody mentioned such huge difference in execution time. Is this normal or am I doing something wrong? If I am what could it be? Thank you