Using SIFT/SURF obj. detection with Android
Hi guys,
I'm working again on a shelf detector (detects product on a shelf and cut them into images) but the last approach (using hist inspection, as mentioned in my previous question) did not suited for my purposes.
So, my tutor told me to try to use an object detection algorithm like SIFT or SURF and use the features extracted from a template image to detect other products.
Because the products differ in their "contents", i.e. logos and drawings on their covers, my idea is to use object detection and then tell to do opencv something like this:
1)get descriptors 2)match all the part of the test image that has a % of keys (not 100% match) > of TOT%
so I have to write an algorithm that selects objects in the test image that has a % of keys matching the template image.
Is this possible with opencv?
Thank you in advance, Panc
hi, thank you for the reply.
I know that sift and surf are nonfree, but I didn't heard that they arent implemented in java, i know that I have to recompile openCV with the nonfree module.
In your opinion, which are the best methodologies for this type of problem? thanks!
"i know that I have to recompile openCV with the nonfree module." - that is unfortunately only half of the job. you also need to modify some intenals of the java wrappers, and then - this would be a local-only solution, since other users of your app will need the opencv-manager, and thus won't get your fix.
thank you so far. I didn't know that is not so simple as I thought. In your opinion which type of methodology can i follow to achieve my goal?
@panc, Did you get the project working?