Loop Closure Detection with Incremental Proximity Graph and Multi-words Quantization

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Abstract

This paper studies the visual loop closure detection problem. The online loop closure detection algorithm is proposed embedded with an incremental visual words codebook. The main novelty of the work lies: 1) To mitigate the coherent quantization error of feature words, a multi-words quantization approach is designed. 2) A hierarchical navigable small world graph is utilized as the codebook structure to alleviate the deficiency of high dimensional search in space partition methods. 3) A complete loop closure detection framework based on tracked word elements is tested and analyzed on several public image datasets. The results validate the computational efficiency of this algorithm.

Original languageEnglish
Title of host publicationASCC 2022 - 2022 13th Asian Control Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1114-1119
Number of pages6
ISBN (Electronic)9788993215236
DOIs
StatePublished - 2022
Event13th Asian Control Conference, ASCC 2022 - Jeju, Korea, Republic of
Duration: 4 May 20227 May 2022

Publication series

NameASCC 2022 - 2022 13th Asian Control Conference, Proceedings

Conference

Conference13th Asian Control Conference, ASCC 2022
Country/TerritoryKorea, Republic of
CityJeju
Period4/05/227/05/22

Keywords

  • online loop-closure detection
  • proximity graph
  • quantization
  • Tracked word

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