# Search and Rescue with Airborne Optical Sectioning

arXiv: https://arxiv.org/abs/2009.08835 · HTML: https://mlsanity.com/paper/2009.08835/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Sep 2020.

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

- [An Autonomous Drone for Search and Rescue in Forests using Airborne Optical Sectioning](https://mlsanity.com/paper/2105.04328/) (2021)
- [The State of Aerial Surveillance: A Survey](https://mlsanity.com/paper/2201.03080/) (2022)
- [Combined Person Classification with Airborne Optical Sectioning](https://mlsanity.com/paper/2106.10077/) (2021)
- [Through-Foliage Tracking with Airborne Optical Sectioning](https://mlsanity.com/paper/2111.06959/) (2021)
- [Inverse Airborne Optical Sectioning](https://mlsanity.com/paper/2207.13344/) (2022)
- [Evaluation of Color Anomaly Detection in Multispectral Images For Synthetic Aperture Sensing](https://mlsanity.com/paper/2211.04293/) (2022)
- [On the Role of Field of View for Occlusion Removal with Airborne Optical Sectioning](https://mlsanity.com/paper/2204.13371/) (2022)
- [Fusion of Single and Integral Multispectral Aerial Images](https://mlsanity.com/paper/2311.17515/) (2023)
- [Stereoscopic Depth Perception Through Foliage](https://mlsanity.com/paper/2310.16120/) (2023)
- [An Autonomous Drone Swarm for Detecting and Tracking Anomalies among Dense Vegetation](https://mlsanity.com/paper/2407.10754/) (2024)
- [DeepForest: Sensing Into Self-Occluding Volumes of Vegetation With Aerial Imaging](https://mlsanity.com/paper/2502.02171/) (2025)
- [Person Recognition in Aerial Surveillance: A Decade Survey](https://mlsanity.com/paper/2511.17674/) (2025)
- [Through-Foliage Surface-Temperature Reconstruction for Early Wildfire Detection](https://mlsanity.com/paper/2511.12572/) (2025)
- [Synthetic Aperture Sensing for Occlusion Removal with Drone Swarms](https://mlsanity.com/paper/2212.14692/) (2022)
- [How Robot Dogs See the Unseeable: Improving Visual Interpretability via Peering for Exploratory Robots](https://mlsanity.com/paper/2511.16262/) (2025)
- [Synthetic Aperture Anomaly Imaging](https://mlsanity.com/paper/2304.13590/) (2023)
- [Reciprocal Visibility](https://mlsanity.com/paper/2402.06991/) (2024)
- [An aerial color image anomaly dataset for search missions in complex forested terrain](https://mlsanity.com/paper/2507.15492/) (2025)
- [Under-Canopy Terrain Reconstruction in Dense Forests Using RGB Imaging and Neural 3D Reconstruction](https://mlsanity.com/paper/2601.22861/) (2026)
- [Vision-Reasoning-Guided Occlusion Removal from Light Fields](https://mlsanity.com/paper/2606.19985/) (2026)

## Abstract (arXiv)

We show that automated person detection under occlusion conditions can be significantly improved by combining multi-perspective images before classification. Here, we employed image integration by Airborne Optical Sectioning (AOS)---a synthetic aperture imaging technique that uses camera drones to capture unstructured thermal light fields---to achieve this with a precision/recall of 96/93%. Finding lost or injured people in dense forests is not generally feasible with thermal recordings, but becomes practical with use of AOS integral images. Our findings lay the foundation for effective future search and rescue technologies that can be applied in combination with autonomous or manned aircraft. They can also be beneficial for other fields that currently suffer from inaccurate classification of partially occluded people, animals, or objects.