Ricerc@Sapienza

Reliable and efficient Visual Place Recognition is
a major building block of modern SLAM systems. Leveraging
on our prior work, in this paper we present a Hamming
Distance embedding Binary Search Tree (HBST) approach
for binary Descriptor Matching and Image Retrieval. HBST
allows for descriptor Search and Insertion in logarithmic time
by exploiting particular properties of binary descriptors. We
support the idea behind our search structure with a thorough
analysis on the exploited descriptor properties and their effects
on completeness and complexity of search and insertion. To
validate our claims we conducted comparative experiments for
HBST and several state-of-the-art methods on a broad range
of publicly available datasets. HBST is available as a compact
open-source C++ header-only library.