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Previous research has shown that in the presence of foliage occlusion, anomaly detection performs significantly better in integral images resulting from synthetic aperture imaging compared to applying it to conventional aerial images. In…

Computer Vision and Pattern Recognition · Computer Science 2023-04-27 Rakesh John Amala Arokia Nathan , Oliver Bimber

Both humans and computational methods struggle to discriminate the depths of objects hidden beneath foliage. However, such discrimination becomes feasible when we combine computational optical synthetic aperture sensing with the human…

Computer Vision and Pattern Recognition · Computer Science 2023-10-26 Robert Kerschner , Rakesh John Amala Arokia Nathan , Rafal Mantiuk , Oliver Bimber

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…

Machine Learning · Computer Science 2020-12-10 David C. Schedl , Indrajit Kurmi , Oliver Bimber

Fully autonomous drones have been demonstrated to find lost or injured persons under strongly occluding forest canopy. Airborne Optical Sectioning (AOS), a novel synthetic aperture imaging technique, together with deep-learning-based…

Computer Vision and Pattern Recognition · Computer Science 2024-10-28 Indrajit Kurmi , David C. Schedl , Oliver Bimber

In this article, we evaluate unsupervised anomaly detection methods in multispectral images obtained with a wavelength-independent synthetic aperture sensing technique, called Airborne Optical Sectioning (AOS). With a focus on search and…

Computer Vision and Pattern Recognition · Computer Science 2022-11-09 Francis Seits , Indrajit Kurmi , Oliver Bimber

Swarms of drones offer an increased sensing aperture, and having them mimic behaviors of natural swarms enhances sampling by adapting the aperture to local conditions. We demonstrate that such an approach makes detecting and tracking…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Rakesh John Amala Arokia Nathan , Sigrid Strand , Daniel Mehrwald , Dmitriy Shutin , Oliver Bimber

Drones will play an essential role in human-machine teaming in future search and rescue (SAR) missions. We present a first prototype that finds people fully autonomously in densely occluded forests. In the course of 17 field experiments…

Computer Vision and Pattern Recognition · Computer Science 2021-05-11 D. C. Schedl , I. Kurmi , O. Bimber

We present Inverse Airborne Optical Sectioning (IAOS) an optical analogy to Inverse Synthetic Aperture Radar (ISAR). Moving targets, such as walking people, that are heavily occluded by vegetation can be made visible and tracked with a…

Computer Vision and Pattern Recognition · Computer Science 2022-07-28 Rakesh John Amala Arokia Nathan , Indrajit Kurmi , Oliver Bimber

The use of drones for aerial cinematography has revolutionized several applications and industries that require live and dynamic camera viewpoints such as entertainment, sports, and security. However, safely controlling a drone while…

Robotics · Computer Science 2019-07-30 Rogerio Bonatti , Cherie Ho , Wenshan Wang , Sanjiban Choudhury , Sebastian Scherer

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…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Rakesh John Amala Arokia Nathan , Matthias Gessner , Nurullah Özkan , Marius Bock , Mohamed Youssef , Maximilian Mews , Björn Piltz , Ralf Berger , Oliver Bimber

We propose an approach to detect flying objects such as UAVs and aircrafts when they occupy a small portion of the field of view, possibly moving against complex backgrounds, and are filmed by a camera that itself moves. Solving such a…

Computer Vision and Pattern Recognition · Computer Science 2015-12-14 Artem Rozantsev , Vincent Lepetit , Pascal Fua

Scattering can rapidly degrade our ability to form an optical image, to the point where only speckle-like patterns can be measured. Truly non-invasive imaging through a strongly scattering obstacle is difficult, and usually reliant on a…

Optics · Physics 2022-10-26 Y. Jauregui-Sánchez , Harry Penketh , Jacopo Bertolotti

We demonstrate how efficient autonomous drone swarms can be in detecting and tracking occluded targets in densely forested areas, such as lost people during search and rescue missions. Exploration and optimization of local viewing…

Robotics · Computer Science 2023-01-02 Rakesh John Amala Arokia Nathan , Indrajit Kurmi , Oliver Bimber

Airborne optical sectioning, an effective aerial synthetic aperture imaging technique for revealing artifacts occluded by forests, requires precise measurements of drone poses. In this article we present a new approach for reducing pose…

Computer Vision and Pattern Recognition · Computer Science 2020-12-17 Indrajit Kurmi , David C. Schedl , Oliver Bimber

A commonly encountered problem is the tracking of a physical object, like a maneuvering ship, aircraft, land vehicle, spacecraft or animate creature carrying a wireless device. The sensor data is often limited and inaccurate observations of…

Systems and Control · Computer Science 2015-03-02 Kevin Judd

Passive RFID tags offer a cost-effective and scalable solution for tracking numerous deployed assets. However, in forested environments, signal attenuation and multipath effects generally limit RFID spatial accuracy to the meter level.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 John Hateley , Sriram Narasimhan , Omid Abari

The ability to know what is hidden around a corner or behind a wall provides a crucial advantage when physically going around the obstacle is impossible or dangerous. Previous solutions to this challenge were constrained e.g. by their…

A robust and efficient anomaly detection technique is proposed, capable of dealing with crowded scenes where traditional tracking based approaches tend to fail. Initial foreground segmentation of the input frames confines the analysis to…

Computer Vision and Pattern Recognition · Computer Science 2013-04-04 Vikas Reddy , Conrad Sanderson , Brian C. Lovell

This research paper addresses the challenge of detecting obscured wildfires (when the fire flames are covered by trees, smoke, clouds, and other natural barriers) in real-time using drones equipped only with RGB cameras. We propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2023-07-04 Uma Meleti , Abolfazl Razi

Occlusion caused by vegetation is an essential problem for remote sensing applications in areas, such as search and rescue, wildfire detection, wildlife observation, surveillance, border control, and others. Airborne Optical Sectioning…

Computer Vision and Pattern Recognition · Computer Science 2022-04-29 Francis Seits , Indrajit Kurmi , Rakesh John Amala Arokia Nathan , Rudolf Ortner , Oliver Bimber
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