This forum is disabled, please visit https://forum.opencv.org
 | 1 | initial version |
Disclaimer: I have not implemented a very good working system of BoW as of yet, but I'm currently working on one.
So far, my findings are these:
1) Good keypoints (obviously). What this means is, keypoints invariant to affine transforms. SIFT/SURF/ORB are good. ORB might be the fastest, but it might not give you the best feature matching quality wise. (Take the hint)
2) Number of clusters. This is the most important. I myself haven't figured out yet what a good number is, given the number of training images. Given that I have N images, I've for now tested and found out that N*100 clusters works well for my purpose (which is not classification, mind you).
I'll update this answer in tomorrow with some links to talk more about the second point. Too many will give you a very hard time detecting/classifying anything. Too less will give you overlapping bad results.
See this, I found it very useful in understanding these problems.
I'll update the answer soon enough with more details. Right now I'm going somewhere.
| | 2 | Suggested edit |
Disclaimer: I have not implemented a very good working system of BoW as of yet, but I'm currently working on one.
So far, my findings are these:
1) Good keypoints (obviously). What this means is, keypoints invariant to affine transforms. SIFT/SURF/ORB are good. ORB might be the fastest, but it might not give you the best feature matching quality wise. (Take the hint)
2) Number of clusters. This is the most important. I myself haven't figured out yet what a good number is, given the number of training images. Given that I have N images, I've for now tested and found out that N*100 clusters works well for my purpose (which is not classification, mind you).
I'll update this answer in tomorrow with some links to talk more about the second point. Too many will give you a very hard time detecting/classifying anything. Too less will give you overlapping bad results.
See this, I found it very useful in understanding these problems.
I'll update the answer soon enough with more details. Right now I'm going somewhere.
