I want to implement Surf feature detector in neural network with python version of opencv.

What I did?

surf feature detector

detector = cv2.SURF(400, 5, 5)

feature detection

k1, d1 = detector.detectAndCompute(img1, None) k2, d2 = detector.detectAndCompute(img2, None)

shape of feature vectors

d1 : 119 x 128

d2 : 129 x 128

neural network creation

nn = cv2.ANN_MLP(np.array([128, 128, 128, 4]), cv2.ANN_MLP_SIGMOID_SYM)

Now, I don't know how to use this varying number of rows in feature vector for different images.Also, do I have to normalize the feature vector before feeding into the neural network?

I want to implement Surf feature detector in neural network with python version of opencv.

What I did?

Now, I don't know how to use this varying number of rows in feature vector for different images.Also, do I have to normalize the feature vector before feeding into the neural network?