Hi,
I have question about using KMeans with SVM. I have implemented an algorithm that extracts desired ROI from video frame with %80 accuracy. The original paper use geometrical approach to decide whether candidate region is a desired region or not desired one. In my school project, I want to improve that geometrical refinment part with local feature based refinment methods. Therefore I want to use both unsupervised and supervised learning methods on extracted ROI to see that it can be improved or not by local features. My desired output is to give an answer to is that desired ROI or not with higher accuracy.
So I setup a dictionary with BowKMeans. But I could not figure out how to combine it with SVM in OpenCV. Can anyone guide me how to do that?
My code is adapted from [here](https://www.codeproject.com/Articles/619039/Bag-of-Features-Descriptor-on-SIFT-Features-with-O) and I also eximined this [link](http://answers.opencv.org/question/24650/how-to-2-class-categolization-using-surfbowsvm/) but could not understand how to do.
↧