Summary: A SIFT Descriptor with Global Context
Eric N. Mortensen
Oregon State University
enm@eecs.oregonstate.edu
Hongli Deng
Oregon State University
deng@eecs.oregonstate.edu
Linda Shapiro
University of Washington
shapiro@cs.washington.edu
Abstract
Matching points between multiple images of a scene is a
vital component of many computer vision tasks. Point
matching involves creating a succinct and discriminative
descriptor for each point. While current descriptors such
as SIFT can find matches between features with unique
local neighborhoods, these descriptors typically fail to
consider global context to resolve ambiguities that can
occur locally when an image has multiple similar regions.
This paper presents a feature descriptor that augments

Source: Anderson, Richard - Department of Computer Science and Engineering, University of Washington at Seattle

Collections: Computer Technologies and Information Sciences