mlsanityData to 14 Oct 2026

Through-Foliage Tracking with Airborne Optical Sectioning

arXiv 2111.06959 ↗First posted 12 Nov 2021cs.CVcited by 13

Not on the map. Why?

Abstract (arXiv)

Detecting and tracking moving targets through foliage is difficult, and for many cases even impossible in regular aerial images and videos. We present an initial light-weight and drone-operated 1D camera array that supports parallel synthetic aperture aerial imaging. Our main finding is that color anomaly detection benefits significantly from image integration when compared to conventional raw images or video frames (on average 97% vs. 42% in precision in our field experiments). We demonstrate, that these two contributions can lead to the detection and tracking of moving people through densely occluding forest.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 7 of its 39 references that are in the map. First posted on arXiv 12 Nov 2021.

Builds on

7 of 39 references.

References · 7

  1. 2021An Autonomous Drone for Search and Rescue in Forests using Airborne Optical Sectioningcited by 32
  2. 2020Search and Rescue with Airborne Optical Sectioningcited by 20
  3. 2019A Statistical View on Synthetic Aperture Imaging for Occlusion Removalcited by 16
  4. 2020Fast Automatic Visibility Optimization for Thermal Synthetic Aperture Visualizationcited by 14
  5. 2020Pose Error Reduction for Focus Enhancement in Thermal Synthetic Aperture Visualizationcited by 13
  6. 2021Combined Person Classification with Airborne Optical Sectioningcited by 13
  7. 2018Image Anomalies: a Review and Synthesis of Detection Methodscited by 10

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 4; 2023: 3; 2024: 2; 2025: 2; 2026: 2.

13 papers.

Sort: