scholarly journals Three-Dimensional Gaze Projection Heat-Mapping of Outdoor Mobile Eye-Tracking Data

2021 ◽  
Vol 5 (1) ◽  
pp. 62-82
Author(s):  
James Simpson
Keyword(s):  
Eye Tracking ◽  
Three Dimensional ◽  
Data Representation ◽  
Tracking Data ◽  
Visualization Technique ◽  
Heat Maps ◽  
Urban Street ◽  
Representation Techniques ◽  
Visual Engagement ◽  
Mobile Eye Tracking

The mobilization of eye-tracking for use outside of the laboratory provides new opportunities for the assessment of pedestrian visual engagement with their surroundings. However, the development of data representation techniques that visualize the dynamics of pedestrian gaze distribution upon the environment they are situated within remains limited. The current study addresses this through highlighting how mobile eye-tracking data, which captures where pedestrian gaze is focused upon buildings along urban street edges, can be mapped as three-dimensional gaze projection heat-maps. This data processing and visualization technique is assessed during the current study along with future opportunities and associated challenges discussed. 

scholarly journals Understanding Visual Engagement with Urban Street Edges along Non-Pedestrianised and Pedestrianised Streets Using Mobile Eye-Tracking

2019 ◽  
Vol 11 (15) ◽  
pp. 4251 ◽  
Author(s):  
James Simpson ◽  
Kevin Thwaites ◽  
Megan Freeth
Keyword(s):  
Eye Tracking ◽  
Urban Streets ◽  
Urban Street ◽  
Everyday Activities ◽  
The Everyday ◽  
Limited Opportunity ◽  
Pedestrian Street ◽  
Empirical Foundation ◽  
Visual Engagement ◽  
Mobile Eye Tracking

Existing knowledge of street edge experience has often been constructed using methods that offer a limited opportunity to gain empirical insight from the first-hand perspective of pedestrians. In order to address this, mobile eye-tracking glasses were used during the current investigation to provide a detailed understanding of pedestrian visual engagement with street edges along both non-pedestrianised and pedestrianised urban streets. Through this, the current study advances empirical knowledge of street edge experience from a perspective that has previously been challenging to capture and quantify. The findings demonstrate that people visually engage with street edge ground floors more than their upper floors, that visual engagement is distributed more towards the street edge on the walked side of non-pedestrianised streets than the opposite side, and that visual engagement with street edges of pedestrianised streets is balanced across both sides. The study findings also highlight how the everyday activities of pedestrians and different streets being walked often influence the amount of visual engagement within these street edge areas. These insights provide a new understanding that develops existing knowledge of pedestrian street edge experience. Significantly, they also provide an empirical foundation from which to examine how design intervention can become more considerate of peoples’ routine use of and experiential engagement with street edges along non-pedestrianised and pedestrianised urban streets.

Eye tracking and tourism research: A systematic literature review

2021 ◽  
pp. 135676672110533
Author(s):  
Georgiana-Denisse Savin ◽  
Cristina Fleșeriu ◽  
Larissa Batrancea
Keyword(s):  
Eye Tracking ◽  
Tracking Data ◽  
Research Papers ◽  
Research Directions ◽  
Heat Maps ◽  
Tourism Research ◽  
Dynamic Stimuli ◽  
Tracking Technique ◽  
The Subject ◽  
Practical Implications

In recent years, the number of studies in tourism using the eye tracking technique has increased and started generating valuable information for both academics and the industry. However, there is a gap in the literature concerning systematic reviews focused on recent articles and their findings. Thus, the aim of this study is to close this gap by systematically analysing 70 research papers tackling the subject of eye tracking in tourism and published in highly ranked tourism journals. The study identifies the most popular topics and trends for eye tracking research, as well as the most used types of visual stimuli, such as exhibitions, restaurant menus, promotional pictures or websites. The study also details on measurements specific for the analysis of eye tracking data, including fixations, saccades and heat maps. Results are emphasized along with their theoretical and practical implications. In addition, we highlight the lack of the use of dynamic stimuli in the existing literature and suggest further research directions using the eye tracking technique.

scholarly journals A system for three-dimensional gaze fixation analysis using eye tracking glasses

2017 ◽  
Vol 5 (4) ◽  
pp. 449-457 ◽  
Author(s):  
Ryo Takahashi ◽  
Hiromasa Suzuki ◽  
Jouh Yeong Chew ◽  
Yutaka Ohtake ◽  
Yukie Nagai ◽  
...  
Keyword(s):  
Eye Tracking ◽  
Three Dimensional ◽  
Prototype System ◽  
Two Dimensional ◽  
Dimensional Model ◽  
Three Dimensional Model ◽  
Heat Maps ◽  
Gaze Fixation ◽  
Tracking Device ◽  
Two Dimensional Images

Abstract Eye tracking is a technology that has quickly become a commonplace tool for evaluating package and webpage design. In such design processes, static two-dimensional images are shown on a computer screen while a subject's gaze where he or she looks is measured via an eye tracking device. The collected gaze fixation data are then visualized and analyzed via gaze plots and heat maps. Such evaluations using two-dimensional images are often too limited to analyze gaze on three-dimensional physical objects such as products because users look at them not from a single point of view but rather from various angles. Therefore in this study we propose methods for collecting gaze fixation data for a three-dimensional model of a given product and visualizing corresponding gaze plots and heat maps also in three dimensions. To achieve our goals, we used a wearable eye-tracking device, i.e., eye-tracking glasses. Further, we implemented a prototype system to demonstrate its advantages in comparison with two-dimensional gaze fixation methods. Highlights Proposing a method for collecting gaze fixation data for a three-dimensional model of a given product. Proposing two visualization methods for three dimensional gaze data; gaze plots and heat maps. Proposed system was applied to two practical examples of hair dryer and car interior.

scholarly journals Using Eye‐Tracking Data to Determine what Biochemistry Students Attend to when Completing a Three‐Dimensional Modeling Activity

2019 ◽  
Vol 33 (S1) ◽  
Author(s):  
Sienna Freeman ◽  
Jenifer Calvert ◽  
Cassidy Terrell ◽  
Adriane Randolph ◽  
Kimberly Linenberger Cortes
Keyword(s):  
Eye Tracking ◽  
Three Dimensional ◽  
Tracking Data ◽  
Three Dimensional Modeling ◽  
Dimensional Modeling

scholarly journals Eye-tracking glasses in face-to-face interactions: Manual versus automated assessment of areas-of-interest

2021 ◽  
Author(s):  
Chiara Jongerius ◽  
T. Callemein ◽  
T. Goedemé ◽  
K. Van Beeck ◽  
J. A. Romijn ◽  
...  
Keyword(s):  
Computer Vision ◽  
Eye Tracking ◽  
Interrater Reliability ◽  
Tracking Data ◽  
Dynamic Interactions ◽  
Area Of Interest ◽  
Gaze Behaviour ◽  
Vision Algorithm ◽  
Areas Of Interest ◽  
Mobile Eye Tracking

AbstractThe assessment of gaze behaviour is essential for understanding the psychology of communication. Mobile eye-tracking glasses are useful to measure gaze behaviour during dynamic interactions. Eye-tracking data can be analysed by using manually annotated areas-of-interest. Computer vision algorithms may alternatively be used to reduce the amount of manual effort, but also the subjectivity and complexity of these analyses. Using additional re-identification (Re-ID) algorithms, different participants in the interaction can be distinguished. The aim of this study was to compare the results of manual annotation of mobile eye-tracking data with the results of a computer vision algorithm. We selected the first minute of seven randomly selected eye-tracking videos of consultations between physicians and patients in a Dutch Internal Medicine out-patient clinic. Three human annotators and a computer vision algorithm annotated mobile eye-tracking data, after which interrater reliability was assessed between the areas-of-interest annotated by the annotators and the computer vision algorithm. Additionally, we explored interrater reliability when using lengthy videos and different area-of-interest shapes. In total, we analysed more than 65 min of eye-tracking videos manually and with the algorithm. Overall, the absolute normalized difference between the manual and the algorithm annotations of face-gaze was less than 2%. Our results show high interrater agreements between human annotators and the algorithm with Cohen’s kappa ranging from 0.85 to 0.98. We conclude that computer vision algorithms produce comparable results to those of human annotators. Analyses by the algorithm are not subject to annotator fatigue or subjectivity and can therefore advance eye-tracking analyses.

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