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2012-10-08 18:26:22 -0600 | commented question | Training of SVM classifier in OpenCV using HOG, SIFT and ORB features Are you sure? For the HOG features I used a cv::Mat in wich I put in the descriptors (in each row the descriptor of one image); so I thought I could do the same with the SIFT: I build (for every image) a vector in wich I put in the descriptors (calculated with the keypoint). Then I push back every vector in a cv::Mat that I use for the training. if, as you say, it doesn't work, can you recommend a better method? thank you very much! |
2012-10-08 07:42:32 -0600 | asked a question | Training of SVM classifier in OpenCV using HOG, SIFT and ORB features I'm trying to train a SVM classifier to recognize pedestrians in a set of 64x128 images. I've already done that using HOG features, and now I need to implement the same thing using SIFT and ORB. Now I have a problem: I can not extract the SIFT features from images, nay, I extract the features but I found out that most of desriptors have a 0 value. This is a piece of the code: Can anyone help me understand how to solve this problem? Many thanks for your help! |