Evaluating User Interfaces Supporting Change Detection in Aerial Images and Aerial Image Sequences

Abstract

Change detection in images taken from the same scene at different times is an important subtask in domains like remote sensing, medical diagnosis, or video surveillance. As human attention is limited, support by computing systems might be beneficial. In this contribution, the benefit of optimized image presentation and the availability of a change mask computed by an automated change detection algorithm is evaluated. In a user study, twelve participants performed change detection in different types of aerial images and aerial image sequences, using parallel side-by-side or alternating flicker image presentation, and performing with and without a change mask. The results show better change detection performance (higher hit rates, shorter completion time, less perceived workload) using the alternating flicker image presentation for the large majority of data sets. With an automated change mask available, the participants’ hit rates increase even more, up to 95% for image pairs and up to 84% for image sequence pairs.