Feature extraction from multiple images in python using SIFT
Key-points extracted from SIFT describe numerous features. If you wish to compare all 400 frames from a video to an image that you have, you will have to make a loop over your process and run SIFT iteratively. This will be computationally expensive.
One method to make this fast would be to read all key-points of these 400 frames and store them into a file so that you don't have to detect them each time you want to compare them with a test image.
This is what I've made from the question that you've asked.
In feature extraction and detection using SIFT, I could extract features from 2 image. But I have 400 frames in video and want to have features from all 400 images in python. Can someone help me out with this?
Thank you.