AR browser for points of interest in disaster response in UAV imagery

Danielle Crowley, Tim McLaughlin, Robin Murphy, Brittany Duncan, Ann McNamara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This work in progress describes AerialAR, a global positioning system (GPS) augmented reality (AR) application for mobile devices that automatically labels points of interest (POI) in unmanned aerial vehicle (UAV) imagery. This has important implications for assisting emergency responders. Existing AR applications for UAVs provide the pilot with navigational situational awareness such as terrain features; AerialAR locates and labels mission-relevant points such as schools that may need to be evacuated or hospitals to transport victims to. Locating POI in UAV imagery poses more challenges than those addressed by typical AR browsers on smartphones. The UAV operates at different altitudes as opposed to handheld devices and the UAV camera can tilt over a wide range of angles rather than simply facing forward. AerialAR overcomes these issues by developing a set of equations that translate UAV telemetry and field of view (fov) into a projection onto a Google Map. The map can then be queried for categories of POI. The current version calculates the POI distance and angles with an average error of 0.04% as compared to the Haversine and Rhumb line equations for the distance between the UAV location projected on the ground and the POI on the Google Map. Future work will complete AerialAR by processing UAV video in real-time on mobile devices.

Original languageEnglish (US)
Title of host publicationCHI EA 2014
Subtitle of host publicationOne of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
Pages2173-2178
Number of pages6
ISBN (Print)9781450324748
DOIs
StatePublished - Jan 1 2014
Event32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014 - Toronto, ON, Canada
Duration: Apr 26 2014May 1 2014

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Other

Other32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014
CountryCanada
CityToronto, ON
Period4/26/145/1/14

Fingerprint

Augmented reality
Unmanned aerial vehicles (UAV)
Disasters
Mobile devices
Labels
Smartphones
Telemetering
Global positioning system
Cameras
Processing

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

Cite this

Crowley, D., McLaughlin, T., Murphy, R., Duncan, B., & McNamara, A. (2014). AR browser for points of interest in disaster response in UAV imagery. In CHI EA 2014: One of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems (pp. 2173-2178). (Conference on Human Factors in Computing Systems - Proceedings). Association for Computing Machinery. https://doi.org/10.1145/2559206.2581171

AR browser for points of interest in disaster response in UAV imagery. / Crowley, Danielle; McLaughlin, Tim; Murphy, Robin; Duncan, Brittany; McNamara, Ann.

CHI EA 2014: One of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2014. p. 2173-2178 (Conference on Human Factors in Computing Systems - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Crowley, D, McLaughlin, T, Murphy, R, Duncan, B & McNamara, A 2014, AR browser for points of interest in disaster response in UAV imagery. in CHI EA 2014: One of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems. Conference on Human Factors in Computing Systems - Proceedings, Association for Computing Machinery, pp. 2173-2178, 32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014, Toronto, ON, Canada, 4/26/14. https://doi.org/10.1145/2559206.2581171
Crowley D, McLaughlin T, Murphy R, Duncan B, McNamara A. AR browser for points of interest in disaster response in UAV imagery. In CHI EA 2014: One of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems. Association for Computing Machinery. 2014. p. 2173-2178. (Conference on Human Factors in Computing Systems - Proceedings). https://doi.org/10.1145/2559206.2581171
Crowley, Danielle ; McLaughlin, Tim ; Murphy, Robin ; Duncan, Brittany ; McNamara, Ann. / AR browser for points of interest in disaster response in UAV imagery. CHI EA 2014: One of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2014. pp. 2173-2178 (Conference on Human Factors in Computing Systems - Proceedings).
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