# Calibrated Keyframe-Segment Selection for Descriptor-Agnostic LiDAR Loop Closure in Repetitive Environments

arXiv: https://arxiv.org/abs/2512.09447 · HTML: https://mlsanity.com/paper/2512.09447/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 34 references that are in the map.
- First posted on arXiv 10 Dec 2025.

## Builds on (most cited first, 15 of 15)

- [Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age](https://mlsanity.com/paper/1606.05830/) (2016)
- [PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition](https://mlsanity.com/paper/1804.03492/) (2018)
- [Scan Context++: Structural Place Recognition Robust to Rotation and Lateral Variations in Urban Environments](https://mlsanity.com/paper/2109.13494/) (2021)
- [OverlapTransformer: An Efficient and Rotation-Invariant Transformer Network for LiDAR-Based Place Recognition](https://mlsanity.com/paper/2203.03397/) (2022)
- [The Newer College Dataset: Handheld LiDAR, Inertial and Vision with Ground Truth](https://mlsanity.com/paper/2003.05691/) (2020)
- [LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place Recognition](https://mlsanity.com/paper/2109.08336/) (2021)
- [SegMatch: Segment based loop-closure for 3D point clouds](https://mlsanity.com/paper/1609.07720/) (2016)
- [Improving Point Cloud Based Place Recognition with Ranking-based Loss and Large Batch Training](https://mlsanity.com/paper/2203.00972/) (2022)
- [LiDAR Iris for Loop-Closure Detection](https://mlsanity.com/paper/1912.03825/) (2019)
- [RING++: Roto-translation Invariant Gram for Global Localization on a Sparse Scan Map](https://mlsanity.com/paper/2210.05984/) (2022)
- [HeLiPR: Heterogeneous LiDAR Dataset for inter-LiDAR Place Recognition under Spatiotemporal Variations](https://mlsanity.com/paper/2309.14590/) (2023)
- [SeqOT: A Spatial-Temporal Transformer Network for Place Recognition Using Sequential LiDAR Data](https://mlsanity.com/paper/2209.07951/) (2022)
- [Large-Scale LiDAR Consistent Mapping using Hierachical LiDAR Bundle Adjustment](https://mlsanity.com/paper/2209.11939/) (2022)
- [FreSCo: Frequency-Domain Scan Context for LiDAR-based Place Recognition with Translation and Rotation Invariance](https://mlsanity.com/paper/2206.12628/) (2022)
- [NDT-Map-Code: A 3D global descriptor for real-time loop closure detection in lidar SLAM](https://mlsanity.com/paper/2307.08221/) (2023)

## Abstract (arXiv)

False LiDAR loop closures can distort pose graphs in repetitive environments, where one query may match several distant places. Genuine revisits, unlike many perceptual aliases, tend to remain consistent across neighboring keyframes. We present Query-Calibrated Segmental Admission (QCSA), a loop-candidate selection method between descriptor retrieval and point-cloud registration. QCSA maps descriptor scores to evidence that distinguishes true loops from hard negatives, accumulates it over short keyframe segments, and admits only the best segment above a threshold fitted to the strongest false segment for each calibration query. The admitted segment forms two local submaps for one Generalized Iterative Closest Point (GICP) registration. QCSA requires pairwise descriptor scores and separate calibration for each descriptor and setting. Across seven descriptors on the SNU Library Dataset (SNULib), QCSA lowers average trajectory error with 53.8% fewer registration attempts than Top-1. With common local submaps and downstream processing on NCLT, it also reduces registration attempts, constraints exceeding the pose-error tolerance, and trajectory error relative to Top-1. HeLiPR Bridge further evaluates repeated outdoor geometry. Our implementation and dataset will be released at: https://github.com/wanderingcar/snu_library_dataset.