invariance in BRIEF. Our main contributions are:
• The addition of a fast and accurate orientation component to FAST.
• The efficient computation of oriented BRIEF features.
• Analysis of variance and correlation of oriented BRIEF features.
• A learning method for de-correlating BRIEF features under rotational invariance, leading to better performance in nearest-neighbor applications.
To validate ORB, we perform experiments that test the properties of ORB relative to SIFT and SURF, for both raw
ORBanefficientalternativetoSIFTorSURF-13439字.docx