TY - JOUR
T1 - Through-Foliage Tracking with Airborne Optical Sectioning
AU - Amala Arokia Nathan, Rakesh John
AU - Kurmi, Indrajit
AU - Schedl, David Christian
AU - Bimber, Oliver
N1 - Publisher Copyright:
Copyright © 2022 Rakesh John Amala Arokia Nathan et al.
PY - 2022/4/22
Y1 - 2022/4/22
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85150209580&partnerID=8YFLogxK
U2 - 10.34133/2022/9812765
DO - 10.34133/2022/9812765
M3 - Article
SN - 2694-1589
VL - 2022
SP - 9812765
JO - Journal of Remote Sensing
JF - Journal of Remote Sensing
M1 - 10.34133/2022/9812765
ER -