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This is not much of an issue with the work that is produced by you, but more of a question regarding the capabilities of your work.
I am currently working on a project that tries to employ machine learning networks to detect, describe, and match keypoints for the purpose of matching 2D robot LiDAR maps. So far, I have been tinkering around with panorama techniques utilising SIFT and the OpenCV Stitcher class, and they both yield successful results only to a certain extent due to the nature of the images being feature-poor.
As such, I would like to ask: Can your cnn-registration work stitch overlapping images? (From what I understand, the registration produced by the code is equivalent to homography that is produced by OpenCV's cv2.findHomography)
If proven successful, I would like to referrence you in my Final Year Project.
The text was updated successfully, but these errors were encountered:
Dear Z. Yang and T. Dan and Y. Yang,
This is not much of an issue with the work that is produced by you, but more of a question regarding the capabilities of your work.
I am currently working on a project that tries to employ machine learning networks to detect, describe, and match keypoints for the purpose of matching 2D robot LiDAR maps. So far, I have been tinkering around with panorama techniques utilising SIFT and the OpenCV Stitcher class, and they both yield successful results only to a certain extent due to the nature of the images being feature-poor.
As such, I would like to ask: Can your cnn-registration work stitch overlapping images? (From what I understand, the registration produced by the code is equivalent to homography that is produced by OpenCV's cv2.findHomography)
If proven successful, I would like to referrence you in my Final Year Project.
The text was updated successfully, but these errors were encountered: