# Inline Photometrically Calibrated Hybrid Visual SLAM

arXiv: https://arxiv.org/abs/2409.16810 · HTML: https://mlsanity.com/paper/2409.16810/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 30 references that are in the map.
- First posted on arXiv 25 Sep 2024.

## Builds on (most cited first, 9 of 9)

- [ORB-SLAM: a Versatile and Accurate Monocular SLAM System](https://mlsanity.com/paper/1502.00956/) (2015)
- [ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM](https://mlsanity.com/paper/2007.11898/) (2020)
- [Direct Sparse Odometry](https://mlsanity.com/paper/1607.02565/) (2016)
- [A Photometrically Calibrated Benchmark For Monocular Visual Odometry](https://mlsanity.com/paper/1607.02555/) (2016)
- [Online Photometric Calibration for Auto Exposure Video for Realtime Visual Odometry and SLAM](https://mlsanity.com/paper/1710.02081/) (2017)
- [Loosely-Coupled Semi-Direct Monocular SLAM](https://mlsanity.com/paper/1807.10073/) (2018)
- [H-SLAM: Hybrid Direct-Indirect Visual SLAM](https://mlsanity.com/paper/2306.07363/) (2023)
- [A Unified Formulation for Visual Odometry](https://mlsanity.com/paper/1903.04253/) (2019)
- [OSPC: Online Sequential Photometric Calibration](https://mlsanity.com/paper/2305.17673/) (2023)

## Abstract (arXiv)

This paper presents an integrated approach to Visual SLAM, merging online sequential photometric calibration within a Hybrid direct-indirect visual SLAM (H-SLAM). Photometric calibration helps normalize pixel intensity values under different lighting conditions, and thereby improves the direct component of our H-SLAM. A tangential benefit also results to the indirect component of H-SLAM given that the detected features are more stable across variable lighting conditions. Our proposed photometrically calibrated H-SLAM is tested on several datasets, including the TUM monoVO as well as on a dataset we created. Calibrated H-SLAM outperforms other state of the art direct, indirect, and hybrid Visual SLAM systems in all the experiments. Furthermore, in online SLAM tested at our site, it also significantly outperformed the other SLAM Systems.