In this paper we propose an approach to embed multi-dimensional continuous 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 a concrete application of our methodology, demonstrating the considered type of continuous cue. Additionally, we conducted a broad quantitative and comparative evaluation on that application, covering five benchmark datasets and several state-of-the-art image retrieval approaches in combination with various binary descriptor types.
2019, 2019 International Conference on Robotics and Automation (ICRA), Pages 5488-5494
Adding Cues to Binary Feature Descriptors for Visual Place Recognition (04b Atto di convegno in volume)
Schlegel Dominik, Grisetti Giorgio
Gruppo di ricerca: Artificial Intelligence and Robotics