Benchmarking Human Performance for Visual Search of Aerial Images.

ABSTRACT: Aerial images are frequently used in geospatial analysis to inform responses to crises and disasters but can pose unique challenges for visual search when they contain low resolution, degraded information about color, and small object sizes. Aerial image analysis is often performed by humans, but machine learning approaches are being developed to complement manual analysis. To date, however, relatively little work has explored how humans perform visual search on these tasks, and understanding this could ultimately help enable human-machine teaming. We designed a set of studies to understand what features of an aerial image make visual search difficult for humans and what strategies humans use when performing these tasks. Across two experiments, we tested human performance on a counting tas

SUBMITTER: Rhodes RE 

PROVIDER: S-EPMC8713551 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature