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Journal of Remote Sensing
Article . 2022 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Journal of Remote Sensing
Article . 2022
Data sources: DOAJ
https://dx.doi.org/10.48550/ar...
Article . 2021
License: CC BY NC ND
Data sources: Datacite
DBLP
Article . 2021
Data sources: DBLP
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Through-Foliage Tracking with Airborne Optical Sectioning

Authors: Nathan, Rakesh John Amala Arokia; Kurmi, Indrajit; Schedl, David C.; Bimber, Oliver;

Through-Foliage Tracking with Airborne Optical Sectioning

Abstract

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.

Keywords

Environmental sciences, FOS: Computer and information sciences, Physical geography, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, GE1-350, GB3-5030

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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3
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18
6
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