# Why are linear SVMs used with HoG feature descriptors?

Ok, almost all applications I have seen that use HoG features use linear svm as classifier. Can someone explain for me why linear svm are chosen and why they give good performance?

Are linear svm chosen because it more simple and easier to train than svms that use polynomial or gaussian kernel and using these kernels is not giving significantly better performance?