# iBoW-LCD: An Appearance-based Loop Closure Detection Approach using Incremental Bags of Binary Words

arXiv: https://arxiv.org/abs/1802.05909 · HTML: https://mlsanity.com/paper/1802.05909/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Feb 2018.

## Built on by (most cited first, 20 of 20)

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- [Monocular visual simultaneous localization and mapping: (r)evolution from geometry to deep learning-based pipelines](https://mlsanity.com/paper/2503.02955/) (2025)
- [Automatic Vocabulary and Graph Verification for Accurate Loop Closure Detection](https://mlsanity.com/paper/2107.14611/) (2021)
- [Active Semantic Localization with Graph Neural Embedding](https://mlsanity.com/paper/2305.06141/) (2023)
- [DK-SLAM: Monocular Visual SLAM with Deep Keypoint Learning, Tracking and Loop-Closing](https://mlsanity.com/paper/2401.09160/) (2024)
- [Training Self-localization Models for Unseen Unfamiliar Places via Teacher-to-Student Data-Free Knowledge Transfer](https://mlsanity.com/paper/2403.10552/) (2024)
- [Semi-supervised Vector-Quantization in Visual SLAM using HGCN](https://mlsanity.com/paper/2207.06738/) (2022)
- [Cross-Camera View-Overlap Recognition](https://mlsanity.com/paper/2208.11661/) (2022)
- [LSGDDN-LCD: An Appearance-based Loop Closure Detection using Local Superpixel Grid Descriptors and Incremental Dynamic Nodes](https://mlsanity.com/paper/2304.03872/) (2023)
- [A Multi-modal Approach to Single-modal Visual Place Classification](https://mlsanity.com/paper/2305.06179/) (2023)
- [Recursive Distillation for Open-Set Distributed Robot Localization](https://mlsanity.com/paper/2312.15897/) (2023)
- [Solving Short-Term Relocalization Problems In Monocular Keyframe Visual SLAM Using Spatial And Semantic Data](https://mlsanity.com/paper/2407.19518/) (2024)
- [LST-SLAM: A Stereo Thermal SLAM System for Kilometer-Scale Dynamic Environments](https://mlsanity.com/paper/2602.20925/) (2026)
- [HuMemSLAM: Efficient Human-Inspired Semantic Place Recognition for Robust Visual SLAM](https://mlsanity.com/paper/2609.17168/) (2026)

## Abstract (arXiv)

In this paper, we introduce iBoW-LCD, a novel appearance-based loop closure detection method. The presented approach makes use of an incremental Bag-of-Words (BoW) scheme based on binary descriptors to retrieve previously seen similar images, avoiding any vocabulary training stage usually required by classic BoW models. In addition, to detect loop closures, iBoW-LCD builds on the concept of dynamic islands, a simple but effective mechanism to group similar images close in time, which reduces the computational times typically associated to Bayesian frameworks. Our approach is validated using several indoor and outdoor public datasets, taken under different environmental conditions, achieving a high accuracy and outperforming other state-of-the-art solutions.