Evaluation of indoor guidance systems using eye tracking in an immersive virtual environment

Zheng

et al. 2018

IJGI

Users more easily become lost in complex indoor environments than in outdoor environments. Users with diverse backgrounds encounter different self-location, route memorization, and route following problems during wayfinding. This study intends to explore gender and age effects on the use of indoor maps for wayfinding in real environments. We used eye-tracking and retrospective verbal protocol methods to conduct a wayfinding experiment in a newly opened building. Statistical data were collected and three findings were obtained. Finding 1: Males had no significant differences with females in indoor self-location, route reading, and route following. However, males paid less visual attention to the landmark and legend than females during route reading. Finding 2: Age-related differences were significant in indoor wayfinding. Younger adults generally outperformed elderly adults in wayfinding in real indoor environments. Finding 3: Gender and age interactive effects were significant in self-location and route memorization. The mean differences of visual attention on the self-location map reading and route memorization between males and females increased with age.

Section: Wayfinding Research In Indoor Environmentsmentioning

confidence: 99%

Gender and Age Differences in Using Indoor Maps for Wayfinding in Real Environments

Zheng

et al. 2018

IJGI

“…The International Workshop on Eye Tracking for Spatial Research launched a wide range of discussion about eye movement research that is not limited to cartography. For example, with mobile eye tracker, both indoor and outdoor way-finding have been further discussed [80][81][82][83].…”

Section: Discussion Related To Current Trendsmentioning

confidence: 99%

Visualizing the Intellectual Structure of Eye Movement Research in Cartography

Yuan

et al. 2016

IJGI

Abstract:Eye movement research is a burgeoning frontier area in cartography that has attracted much attention from cartographers. However, the substantial amount of relevant literature poses a challenge for researchers aiming to obtain a rapid understanding of the intellectual structure of this research field. The purpose of this paper is to introduce the use of bibliometric analysis methods and multiple visual metaphors to visualize the intellectual structure of eye movement research in cartography, including the classic literature, research theme clusters, and research hotspots, etc. We also explain the use of geovisualization method, which can efficiently represent the spatial distribution of scientific power. Although the analysis results may not fully describe the whole research field, this method is generally applicable. We hope that it will not only help researchers to quickly grasp the evolution and trends of this research field, but will also become a novel method of merging geovisualization with knowledge visualization.

“…In addition, eye-tracking data assist researchers in analyzing gaze performance in quantitative ways [38]. For instance, eye-tracking data have been used as a rich data source for mining visual attention to landmarks during wayfinding [39,40]. Only recently have eye-tracking data been used by Jia [14] to calculate the visual attractiveness of landmarks.…”

Section: Eye-tracking For Task Differences In Landmark Saliencementioning

confidence: 99%

“…The use of eye-tracking data to generate a landmark salience model (visual, semantic and structural attractiveness) has not been tested. Researchers have applied the eye-tracking method to analyze semantic and spatial information [21,40]. For example, Raubal [7] proposed that city maps and street graphs are complemented with images and content databases, which could provide visual data as well as semantic and structural data.…”

Section: Eye-tracking For Task Differences In Landmark Saliencementioning

confidence: 99%

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

Zheng

et al. 2020

IJGI

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.