Why is there only one support vector in OpenCV's SVM

I am using libsvm to train a SVM with hog features. The model file has n support vectors. But when I try to use it in OpenCV's SVM I found that there is o开发者_运维技巧nly one vector in OpenCV's model. How does OpenCV do it??

I guess libsvm stores support vectors, whereas opencv just uses a weight vector to store the hyperplane (one vector + one scalar suffices to describe a plane) - you can get there from the decision function using the support vectors by swapping sum and scalar product.

Here is the explanation from Learning OpenCV3: In the case of linear SVM, all the support vectors for each decision plane can be compressed into a single vector that will basically describe the separating hyperplane.