Research on Generating an Indoor Landmark Salience Model for Self-Location and Spatial Orientation from Eye-Tracking Data

Abstract

Landmarks play an essential role in wayfinding and are closely related to cognitive processes. Eye-tracking data contain massive amounts of information that can be applied to discover the cognitive behaviors during wayfinding; however, little attention has been paid to applying such data to calculating landmark salience models. This study proposes a method for constructing an indoor landmark salience model based on eye-tracking data. First, eye-tracking data are taken to calculate landmark salience for self-location and spatial orientation tasks through partial least squares regression (PLSR). Then, indoor landmark salience attractiveness (visual, semantic and structural) is selected and trained by landmark salience based on the eye-tracking data. Lastly, the indoor landmark salience model is generated by landmark salience attractiveness. Recruiting 32 participants, we designed a laboratory eye-tracking experiment to construct and test the model. Finding 1 proves that our eye-tracking data-based modelling method is more accurate than current weighting methods. Finding 2 shows that significant differences in landmark salience occur between two tasks; thus, it is necessary to generate a landmark salience model for different tasks. Our results can contribute to providing indoor maps for different tasks.

Designing mobile spatial navigation systems from the user's perspective: An interdisciplinary review

“…In these cases, wayfinding trajectories, specifics of application use, familiar environment knowledge, and learning of new environments could all be measured or manipulated to increase insights into behavior-system-environment interactions. For example, mobile eye tracking has been proposed as a rich tool to measure individuals' dynamic wayfinding behaviors using navigation systems (Kiefer et al, 2012(Kiefer et al, , 2017 and to model gazebased landmark salience (Krukar, Mavros, et al, 2020;Wang et al, 2020). In addition, MapRecorder is a recently developed tool that provides insights into interaction with common navigation systems such as Google Maps (Savino et al, 2020) The effects of navigation systems on navigational processes throughout the lifespan also need to be further investigated (Unrau & Kray, 2019).…”

VES: A Mixed-Reality Development Platform of Navigation Systems for Blind and Visually Impaired

“…Occasionally, this was complemented by sensors that monitored physiological data such as heart rate or electrodermal activity as stress indicators along the route [ 19 ]. In parallel, spatial perception and cognition experiments with normal-sighted individuals took advantage of eye-tracking to study landmark salience [ 20 ].…”

To Drive or to Be Driven? The Impact of Autopilot, Navigation System, and Printed Maps on Driver’s Cognitive Workload and Spatial Knowledge

“…Landmark knowledge relates to knowledge about distinct objects or scenes that are eye-catching or salient in the environment. Landmarks were found to play a significant role in way-finding strategies, spatial decision making, and orientation in space [2,9,26,27]. In contrast, route knowledge includes the sequences of view-action pairs, where individuals associate a certain action with a decision point [28] (e.g., "turn right at the shopping mall").…”