Image hashing for loop closing in underwater visual SLAM

Authors

  • Francisco Bonin Font
  • Antoni Burguera Burguera
  • Gabriel Antonio Oliver Codina

DOI:

https://doi.org/10.5821/iwp.2021.21.14807

Abstract

This article presents an experimental assessment of a hash-based loop closure detection methodology specially addressed to Multi-robot underwater visual Simultaneous Localization and Mapping (SLAM). This methodology uses two diferent top quality image global descriptors, one learned (NetVLAD) and one handcrafted (HALOC). Complete tests were done to compare the performance of both hashing techniques applied in an extensive set of real underwater imagery.

Issue

No. 21 (2021)

Section

Articles

License

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