Ideas for extracting features of an object using keypoints of image

Question

I'll be appreciated if you help me to create a feature vector of an simple object using keypoints. For now, I use ETH-80 dataset, objects have an almost blue background and pictures are took from different views. Like this:

After creating a feature vector, I want to train a neural network with this vector and use that neural network to recognize an input image of an object. I don't want make it complex, input images will be as simple as train images. I asked similar questions before, some one suggested using average value of 20x20 neighborhood of keypoints. I tried it, It seems it's not working with ETH-80 images, because of different views of images. It's why I asked another question.

Answer 1

SURF or SIFT. Look for interest point detectors. A MATLAB SIFT implementation is freely available.

Update: Object Recognition from Local Scale-Invariant Features