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Title: Hierarchically Organized Computer Vision in Support of Multi-Faceted Search for Missing Persons
Missing person searches are typically initiated with a description of a person that includes their age, race, clothing, and gender, possibly supported by a photo. Unmanned Aerial Systems (sUAS) imbued with Computer Vision (CV) capabilities, can be deployed to quickly search an area to find the missing person; however, the search task is far more difficult when a crowd of people is present, and only the person described in the missing person report must be identified. It is particularly challenging to perform this task on the potentially limited resources of an sUAS. We therefore propose AirSight, as a new model that hierarchically combines multiple CV models, exploits both onboard and off-board computing capabilities, and engages humans interactively in the search. For illustrative purposes, we use AirSight to show how a person's image, extracted from an aerial video can be matched to a basic description of the person. Finally, as a work-in-progress paper, we describe ongoing efforts in building an aerial dataset of partially occluded people and physically deploying AirSight on our sUAS.  more » « less
Award ID(s):
1931962
NSF-PAR ID:
10468155
Author(s) / Creator(s):
;
Publisher / Repository:
2023 IEEE 17th International Conference on Automatic Face and Gesture Recognition (FG)
Date Published:
Volume:
2023
ISBN:
979-8-3503-4544-5
Page Range / eLocation ID:
1 to 7
Subject(s) / Keyword(s):
aerial search drones computer vision
Format(s):
Medium: X
Location:
Waikoloa Beach, HI, USA
Sponsoring Org:
National Science Foundation
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