# HDRFusion: HDR SLAM using a low-cost auto-exposure RGB-D sensor

arXiv: https://arxiv.org/abs/1604.00895 · HTML: https://mlsanity.com/paper/1604.00895/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Apr 2016.

## Built on by (most cited first, 1 of 1)

- [Multi-Session Visual SLAM for Illumination Invariant Re-Localization in Indoor Environments](https://mlsanity.com/paper/2103.03827/) (2021)

## Abstract (arXiv)

We describe a new method for comparing frame appearance in a frame-to-model 3-D mapping and tracking system using an low dynamic range (LDR) RGB-D camera which is robust to brightness changes caused by auto exposure. It is based on a normalised radiance measure which is invariant to exposure changes and not only robustifies the tracking under changing lighting conditions, but also enables the following exposure compensation perform accurately to allow online building of high dynamic range (HDR) maps. The latter facilitates the frame-to-model tracking to minimise drift as well as better capturing light variation within the scene. Results from experiments with synthetic and real data demonstrate that the method provides both improved tracking and maps with far greater dynamic range of luminosity.