I've also asked this question here:https://cs.stackexchange.com/questions/77884/are-the-hog-features-of-the-images-good-enough-to-do-image-classification-alone
I've been working on classifying human poses like the pictures below. For that, I'm computing HOG features, and while in MATLAB, after using the command extractHOGfeatures, it's giving me 1764 HOG features, I also notice that maximum variance of all the 1764 HOG features are as low as 0.04 for a sample size of 2660, meaning the HOG features aren't probably changing much from sample-to-sample. My questions are:
1) why do you think we're getting low variances for HOG features? 2) what could we intuitively say about HOG features of these pose images? Are they good or interesting enough to classify images alone?