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An aerial color image anomaly dataset for search missions in complex forested terrain

Computer Vision and Pattern Recognition 2025-07-22 v1

Abstract

After a family murder in rural Germany, authorities failed to locate the suspect in a vast forest despite a massive search. To aid the search, a research aircraft captured high-resolution aerial imagery. Due to dense vegetation obscuring small clues, automated analysis was ineffective, prompting a crowd-search initiative. This effort produced a unique dataset of labeled, hard-to-detect anomalies under occluded, real-world conditions. It can serve as a benchmark for improving anomaly detection approaches in complex forest environments, supporting manhunts and rescue operations. Initial benchmark tests showed existing methods performed poorly, highlighting the need for context-aware approaches. The dataset is openly accessible for offline processing. An additional interactive web interface supports online viewing and dynamic growth by allowing users to annotate and submit new findings.

Keywords

Cite

@article{arxiv.2507.15492,
  title  = {An aerial color image anomaly dataset for search missions in complex forested terrain},
  author = {Rakesh John Amala Arokia Nathan and Matthias Gessner and Nurullah Özkan and Marius Bock and Mohamed Youssef and Maximilian Mews and Björn Piltz and Ralf Berger and Oliver Bimber},
  journal= {arXiv preprint arXiv:2507.15492},
  year   = {2025}
}

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17 pages