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.
Adding Cues to Binary Feature Descriptors for Visual Place Recognition / Schlegel, Dominik; Grisetti, Giorgio. - (2019), pp. 5488-5494. (Intervento presentato al convegno 2019 International Conference on Robotics and Automation, ICRA 2019 tenutosi a Montreal; Canada;) [10.1109/ICRA.2019.8793753].
Adding Cues to Binary Feature Descriptors for Visual Place Recognition
SCHLEGEL, DOMINIK
Primo
;Grisetti, Giorgio
Secondo
2019
Abstract
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.File | Dimensione | Formato | |
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