 | 1 | initial version |
I posted this message on StackOverflow and since there seems that nobody wants i thought i might share it here maybe i can get some help. This is the link: http://stackoverflow.com/questions/17783146/object-recognition-using-opencv4android
Any help is appreciated.
| | 2 | No.2 Revision |
I posted this message on StackOverflow and since there seems that nobody wants knows, i thought i might share it here maybe i can get some help.
This is the link:
http://stackoverflow.com/questions/17783146/object-recognition-using-opencv4android
Any help is appreciated.
| | 3 | No.3 Revision |
I posted this message on StackOverflow and since there seems that nobody knows, i thought i might share it here maybe i can get some help.
help.
This is the link:
http://stackoverflow.com/questions/17783146/object-recognition-using-opencv4android
0 down vote favorite
I am trying to make an app which should recognize hand gestures on Android using opencv. The reason for this is that i want to be able to click on augmented reality bubbles from Metaio(if by chance someone has worked with Metaio) using hand gestures. My approach was to track my hand and recognize the gesture. As for the detector i tested Orb (almost decided on since i didn't find any better),FAST, BRISK (for some unknown reason was poor - 800 ms - worse than SURF - 200 ms)SURF and out of all of them only ORB and FAST gave good results, as for the descriptor either FREAK or ORB again. The results for the descriptors were good, around 80 ms - FREAK and 35 ms for ORB , therefore i would say this part is almost done(Final tests are not yet finished). Considering the latter part closed, i am worried about the matching part. I made a few tests so far - i used BruteForceMatcher and FlannBasedMatcher - and the results were not so good, meaning on pc it needed more than 2-3 secs (one can argue in the case of FlannBasedMatcher that i only trained the FlannBasedMatcher with 30-40 different gestures). My questions for you would be :
Is it possible to achieve on android a matching under 100-200ms? - meaning the entire process to take less than 300ms.
If it's possible, what would be the approach? - i thought of either using BOW + SVM or ANN (i must state i don't have here a clear picture in my hand (i only read this paper http://www.morethantechnical.com/2011/08/25/a-simple-object-classifier-with-bag-of-words-using-opencv-2-3-w-code/)).
Any help other suggestion which is helpful would be really appreciated.
