Scanpath Analysis of Fused Multi-Sensor Images with Luminance Change: A Pilot Study

Abstract

Image fusion is the process of combining images of differing modalities, such as visible and infrared (IR) images. Significant work has recently been carried out comparing methods of fused image assessment, with findings strongly suggesting that a task-centred approach would be beneficial to the assessment process. The current paper reports a pilot study analysing eye movements of participants involved in four tasks. The first and second tasks involved tracking a human figure wearing camouflage clothing walking through thick undergrowth at light and dark luminance levels, whilst the third and fourth task required tracking an individual in a crowd, again at two luminance levels. Participants were shown the original visible and IR images individually, pixel-averaged, contrast pyramid, and dual-tree complex wavelet fused video sequences. They viewed each display and sequence three times to compare inter-subject scanpath variability. This paper describes the initial analysis of the eye-tracking data gathered from the pilot study. These were also compared with computational metric assessment of the image sequences