文件名称：ORB_an efficient alternative to SIFT or SURF
文件大小：2.25MB
文件格式：PDF
更新时间：2016-11-16 04:38:44
ORB SIFT SURF
Feature matching is at the base of many computer vision problems, such as object recognition or structure from motion. Current methods rely on costly descriptors for detection and matching. In this paper, we propose a very fast binary descriptor based on BRIEF, called ORB, which is rotation invariant and resistant to noise. We demonstrate through experiments how ORB is at two orders of magnitude faster than SIFT, while peiforming as well in many situations. The efficiency is tested on several real-world applications, including object detection and patch-tracking on a smart phone.