# IFTD: Image Feature Triangle Descriptor for Loop Detection in Driving Scenes

arXiv: https://arxiv.org/abs/2406.07937 · HTML: https://mlsanity.com/paper/2406.07937/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 31 references that are in the map.
- First posted on arXiv 12 Jun 2024.

## Builds on (most cited first, 17 of 17)

- [ORB-SLAM: a Versatile and Accurate Monocular SLAM System](https://mlsanity.com/paper/1502.00956/) (2015)
- [VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator](https://mlsanity.com/paper/1708.03852/) (2017)
- [LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping](https://mlsanity.com/paper/2007.00258/) (2020)
- [FAST-LIO2: Fast Direct LiDAR-inertial Odometry](https://mlsanity.com/paper/2107.06829/) (2021)
- [OverlapNet: Loop Closing for LiDAR-based SLAM](https://mlsanity.com/paper/2105.11344/) (2021)
- [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)
- [LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAM](https://mlsanity.com/paper/2103.05056/) (2021)
- [LiDAR Iris for Loop-Closure Detection](https://mlsanity.com/paper/1912.03825/) (2019)
- [Direct LiDAR-Inertial Odometry: Lightweight LIO with Continuous-Time Motion Correction](https://mlsanity.com/paper/2203.03749/) (2022)
- [STD: Stable Triangle Descriptor for 3D place recognition](https://mlsanity.com/paper/2209.12435/) (2022)
- [R2LIVE: A Robust, Real-time, LiDAR-Inertial-Visual tightly-coupled state Estimator and mapping](https://mlsanity.com/paper/2102.12400/) (2021)
- [Robust Place Recognition using an Imaging Lidar](https://mlsanity.com/paper/2103.02111/) (2021)
- [Contour Context: Abstract Structural Distribution for 3D LiDAR Loop Detection and Metric Pose Estimation](https://mlsanity.com/paper/2302.06149/) (2023)
- [SR-LIO: LiDAR-Inertial Odometry with Sweep Reconstruction](https://mlsanity.com/paper/2210.10424/) (2022)
- [SR-LIVO: LiDAR-Inertial-Visual Odometry and Mapping with Sweep Reconstruction](https://mlsanity.com/paper/2312.16800/) (2023)
- [Semi-Elastic LiDAR-Inertial Odometry](https://mlsanity.com/paper/2307.07792/) (2023)

## Abstract (arXiv)

In this work, we propose a fast and robust Image Feature Triangle Descriptor (IFTD) based on the STD method, aimed at improving the efficiency and accuracy of place recognition in driving scenarios. We extract keypoints from BEV projection image of point cloud and construct these keypoints into triangle descriptors. By matching these feature triangles, we achieved precise place recognition and calculated the 4-DOF pose estimation between two keyframes. Furthermore, we employ image similarity inspection to perform the final place recognition. Experimental results on three public datasets demonstrate that our IFTD can achieve greater robustness and accuracy than state-of-the-art methods with low computational overhead.