Hello All,
I am a student and currently doing my project in the field of Image recognition using Feature Point detectors and descriptors. I have no prior knowledge on the topics of Image recognition techniques before starting of this project and then I have researched on the available detectors and descriptors and the differences between them. Finally, I have opted out to work with the ORB detectors and descriptors for Image recognition (If it didn't worked according to my requiremnets then I would like to go out with the BRISK later).
As of now am in a stage of getting the results for Image recognition using ORB. At this Point, I was thinking of to use Gaussian Filters in my code so that I can get better results even though the Input Image is a bit blur.
My questions:
1) Is it possible to use Gaussian filters with ORB to get much better results for Image recognition?
2) When I read the paper on ORB I came to know that the lines below
FAST does not produce a measure of cornerness, and we have found that it has large responses along edges. We employ a Harris corner measure [11] to order the FAST keypoints. For a target number N of keypoints, we first set the threshold low enough to get more than N keypoints, then order them according to the Harris measure, and pick the top N points.
FAST does not producemulti-scale features. We employ a scale pyramid of the image, and produce FAST Features (filtered by Harris) at each level in the pyramid.
ORB provides the Harris Corner inorder to detect the corners in an image and is it worth for me to use Gaussian Filters along with ORB?
3) ORB uses only Harris Corner to detect the corners or any other?
Please let me know about this and just enlighten me on the above mentioned questions.