Computer vision enhances mobile eye-tracking to expose expert cognition in natural-scene visual-search tasks

Tommy P. Keane; Nathan D. Cahill; John A. Tarduno; Robert A. Jacobs; Jeff B. Pelz

doi:10.1117/12.2040493

25 February 2014 Computer vision enhances mobile eye-tracking to expose expert cognition in natural-scene visual-search tasks

Tommy P. Keane, Nathan D. Cahill, John A. Tarduno, Robert A. Jacobs, Jeff B. Pelz

Author Affiliations +

Proceedings Volume 9014, Human Vision and Electronic Imaging XIX; 90140F (2014) https://doi.org/10.1117/12.2040493
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

Abstract

Mobile eye-tracking provides the fairly unique opportunity to record and elucidate cognition in action. In our research, we are searching for patterns in, and distinctions between, the visual-search performance of experts and novices in the geo-sciences. Traveling to regions resultant from various geological processes as part of an introductory field studies course in geology, we record the prima facie gaze patterns of experts and novices when they are asked to determine the modes of geological activity that have formed the scene-view presented to them. Recording eye video and scene video in natural settings generates complex imagery that requires advanced applications of computer vision research to generate registrations and mappings between the views of separate observers. By developing such mappings, we could then place many observers into a single mathematical space where we can spatio-temporally analyze inter- and intra-subject fixations, saccades, and head motions. While working towards perfecting these mappings, we developed an updated experiment setup that allowed us to statistically analyze intra-subject eye-movement events without the need for a common domain. Through such analyses we are finding statistical differences between novices and experts in these visual-search tasks. In the course of this research we have developed a unified, open-source, software framework for processing, visualization, and interaction of mobile eye-tracking and high-resolution panoramic imagery.

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Tommy P. Keane, Nathan D. Cahill, John A. Tarduno, Robert A. Jacobs, and Jeff B. Pelz "Computer vision enhances mobile eye-tracking to expose expert cognition in natural-scene visual-search tasks", Proc. SPIE 9014, Human Vision and Electronic Imaging XIX, 90140F (25 February 2014); https://doi.org/10.1117/12.2040493

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