Papers › Adding Cues to Binary Feature Descriptors for Visual Place Recognition
Adding Cues to Binary Feature Descriptors for Visual Place Recognition
Dominik Schlegel, Giorgio Grisetti
In this paper we propose an approach to embed continuous and selector cues in binary feature descriptors used for visual place recognition. The embedding is achieved by extending each feature descriptor with a binary string that encodes a cue and supports the Hamming distance metric. Augmenting the descriptors in such a way has the advantage of being transparent to the procedure used to compare them. We present two concrete applications of our methodology, demonstrating the two considered types of cues. In addition to that, we conducted on these applications a broad quantitative and comparative evaluation covering five benchmark datasets and several state-of-the-art image retrieval approaches in combination with various binary descriptor types.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections