Improving Binary Feature Descriptors Using Spatial Structure
Michal Kottman · 2013
Feature descriptors are used to describe salient image keypoints in a way that allows easy matching between different features. Modern binary descriptors use bit vectors to store this information. These descriptors use simple comparisons between different keypoint parts to construct the bit vector. What they differ in is the arrangement of keypoint parts, ranging from random selection in BRIEF descriptor to human vision-like pattern in the FREAK descriptor. A recent descriptor D-Nets shows that linebased arrangement improves recognition rate for feature matching. We show that by extending the comparisons to line arrangement better describes the spatial structure surrounding the keypoint and performs better in standard feature description benchmarks.