Evaluation of Technologies That Help to Identify Hazards for Cyclists in Cities

2020 ◽  
pp. 155-171
Author(s):  
Christine Chaloupka ◽  
Ralf Risser ◽  
Elisabeth Füssl
Keyword(s):  
Visual Attention ◽  
Eye Tracking ◽  
Peripheral Vision ◽  
Complete Picture ◽  
Development Work ◽  
Technological Method ◽  
Points Of Interest ◽  
Verbal Data ◽  
Mobile Eye Tracking

How do people look at sites and places and perceive details? Studies are referred dealing with the looking behaviour of cyclists, under the assumption that the method used could also be applied for assessing looking behaviour of tourists and to learn more about risks for cyclists. In the frame of a naturalistic cycling study in Austria, among others, a method should be developed that would help to find out where bicyclists direct their visual attention on their ways. Use was made of mobile eye tracking glasses. Results will be shown of the development work that demonstrate that points of interest can be identified via the detection of gaze plots of samples of cyclists. No technology helps to register what is perceived by peripheral vision which would give a more complete picture of reality. Any technological method that today registers where cyclists, or customers, or visitors direct their attention to has to be completed with verbal data from interviews, questionnaires, etc. in order to assure themselves of what really has been perceived.

scholarly journals Automatic Visual Attention Detection for Mobile Eye Tracking Using Pre-Trained Computer Vision Models and Human Gaze

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4143
Author(s):  
Michael Barz ◽  
Daniel Sonntag
Keyword(s):  
Deep Learning ◽  
Visual Attention ◽  
Eye Tracking ◽  
Performance Metrics ◽  
Evaluation Framework ◽  
Detection Methods ◽  
Manual Annotation ◽  
Learning Models ◽  
Areas Of Interest ◽  
Mobile Eye Tracking

Processing visual stimuli in a scene is essential for the human brain to make situation-aware decisions. These stimuli, which are prevalent subjects of diagnostic eye tracking studies, are commonly encoded as rectangular areas of interest (AOIs) per frame. Because it is a tedious manual annotation task, the automatic detection and annotation of visual attention to AOIs can accelerate and objectify eye tracking research, in particular for mobile eye tracking with egocentric video feeds. In this work, we implement two methods to automatically detect visual attention to AOIs using pre-trained deep learning models for image classification and object detection. Furthermore, we develop an evaluation framework based on the VISUS dataset and well-known performance metrics from the field of activity recognition. We systematically evaluate our methods within this framework, discuss potentials and limitations, and propose ways to improve the performance of future automatic visual attention detection methods.

scholarly journals Students in sight: Using mobile eye-tracking to investigate mathematics teachers’ gaze behaviour during task instruction-giving

2021 ◽  
Vol 9 (4) ◽  
pp. 92-115
Author(s):  
Olli Maatta ◽  
Nora McIntyre ◽  
Jussi Palomäki ◽  
Markku S. Hannula ◽  
Patrik Scheinin ◽  
...  
Keyword(s):  
Eye Tracking ◽  
Mathematical Problem ◽  
Task Instruction ◽  
Task Instructions ◽  
Video Recordings ◽  
Gaze Patterns ◽  
Gaze Behaviour ◽  
Geometry Problem ◽  
Verbal Data ◽  
Mobile Eye Tracking

Abstract Mobile eye-tracking research has provided evidence both on teachers' visual attention in relation to their intentions and on teachers’ student-centred gaze patterns. However, the importance of a teacher’s eye-movements when giving instructions is unexplored. In this study we used mobile eye-tracking to investigate six teachers’ gaze patterns when they are giving task instructions for a geometry problem in four different phases of a mathematical problem-solving lesson. We analysed the teachers’ eye-tracking data, their verbal data, and classroom video recordings. Our paper brings forth a novel interpretative lens for teacher’s pedagogical intentions communicated by gaze during teacher-led moments such as when introducing new tasks, reorganizing the social structures of students for collaboration, and lesson wrap-ups. A change in the students’ task changes teachers’ gaze patterns, which may indicate a change in teacher’s pedagogical intention. We found that teachers gazed at students throughout the lesson, whereas teachers’ focus was at task-related targets during collaborative instruction-giving more than during the introductory and reflective task instructions. Hence, we suggest two previously not detected gaze types: contextualizing gaze for task readiness and collaborative gaze for task focus to contribute to the present discussion on teacher gaze

scholarly journals Exploring the Awe-some: Mobile eye-tracking insights into awe in a science museum

2020 ◽  
Author(s):  
Sheila Krogh-Jespersen ◽  
Kimberly A Quinn ◽  
William Leo Donald Krenzer ◽  
Christine Thi Nguyen ◽  
Jana Greenslit ◽  
...  
Keyword(s):  
Visual Attention ◽  
Eye Tracking ◽  
Informal Learning ◽  
Emotional Experience ◽  
Science Museum ◽  
Exhibit Design ◽  
Informal Learning Environments ◽  
Survey Responses ◽  
Tracking Technology ◽  
Mobile Eye Tracking

Informal learning environments provide the opportunity to study guests’ experiences as they engage with exhibits specifically designed to invoke the emotional experience of awe. The current paper presents insight gained by using both traditional survey measures and innovative mobile eye-tracking technology to examine guests’ experiences of awe in a science museum. We present results for guests’ visual attention in two exhibit spaces, one chosen for its potential to evoke positive awe and one for negative awe, and examine associations between visual attention and survey responses with regard to different facets of awe. In this exploratory study, we find relationships between how guests attend to features within an exhibit space (e.g., signage) and their feelings of awe. We discuss implications of using both methods concurrently to shed new light on exhibit design, and more generally for working in transdisciplinary multimethod teams to move scientific knowledge and application forward.

scholarly journals Visual attention towards food during unplanned purchases – A pilot study using mobile eye tracking technology

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247755
Author(s):  
Gerrit Hummel ◽  
Saskia Maier ◽  
Maren Baumgarten ◽  
Cora Eder ◽  
Patrick Thomas Strubich ◽  
...  
Keyword(s):  
Pilot Study ◽  
Energy Density ◽  
Visual Attention ◽  
Eye Tracking ◽  
Weight Status ◽  
Field Research ◽  
Purchase Behavior ◽  
Food Perception ◽  
Tracking Devices ◽  
Mobile Eye Tracking

This pilot study aims to investigate the relationships between consumers’ weight status, energy density of food and visual attention towards food during unplanned purchase behavior in a real-world environment. After more than a decade of intensive experimental eye tracking research on food perception, this pilot study attempts to link experimental and field research in this area. Shopping trips of participants with different weight status were recorded with mobile eye tracking devices and their unplanned purchase behavior was identified and analyzed. Different eye movement measurements for initial orientation and maintained attention were analyzed. Differences in visual attention caused by energy density of food were found. There was a tendency across all participants to look at low energy density food longer and more often.

scholarly journals Investigating Visual Attention toward Foods in a Salad Buffet with Mobile Eye Tracking

2021 ◽  
pp. 104290
Author(s):  
Marjaana Puurtinen ◽  
Ulla Hoppu ◽  
Sari Puputti ◽  
Saila Mattila ◽  
Mari Sandell
Keyword(s):  
Visual Attention ◽  
Eye Tracking ◽  
Mobile Eye Tracking

Do you see what I mean?: Using mobile eye tracking to capture parent–child dynamics in the context of anxiety risk

2021 ◽  
pp. 1-16
Author(s):  
Leigha A. MacNeill ◽  
Xiaoxue Fu ◽  
Kristin A. Buss ◽  
Koraly Pérez-Edgar
Keyword(s):  
Eye Tracking ◽  
Positive Reinforcement ◽  
Parental Behavior ◽  
Anxiety Level ◽  
Eye Tracker ◽  
Fine Grained ◽  
Controlling Parenting ◽  
Attractor Strength ◽  
Child Age ◽  
Mobile Eye Tracking

Abstract Temperamental behavioral inhibition (BI) is a robust endophenotype for anxiety characterized by increased sensitivity to novelty. Controlling parenting can reinforce children's wariness by rewarding signs of distress. Fine-grained, dynamic measures are needed to better understand both how children perceive their parent's behaviors and the mechanisms supporting evident relations between parenting and socioemotional functioning. The current study examined dyadic attractor patterns (average mean durations) with state space grids, using children's attention patterns (captured via mobile eye tracking) and parental behavior (positive reinforcement, teaching, directives, intrusion), as functions of child BI and parent anxiety. Forty 5- to 7-year-old children and their primary caregivers completed a set of challenging puzzles, during which the child wore a head-mounted eye tracker. Child BI was positively correlated with proportion of parent's time spent teaching. Child age was negatively related, and parent anxiety level was positively related, to parent-focused/controlling parenting attractor strength. There was a significant interaction between parent anxiety level and child age predicting parent-focused/controlling parenting attractor strength. This study is a first step to examining the co-occurrence of parenting behavior and child attention in the context of child BI and parental anxiety levels.

scholarly journals Visual Attention Software: A New Tool for Understanding the “Subliminal” Experience of the Built Environment

2021 ◽  
Vol 11 (13) ◽  
pp. 6197
Author(s):  
Alexandros A. Lavdas ◽  
Nikos A. Salingaros ◽  
Ann Sussman
Keyword(s):  
Visual Attention ◽  
Eye Tracking ◽  
Wearable Sensors ◽  
Computer Gaming ◽  
Geometric Patterns ◽  
Relative Design ◽  
Fixation Points ◽  
High Degree ◽  
Artificial Intelligence Application ◽  
Intelligence Application

Eye-tracking technology is a biometric tool that has found many commercial and research applications. The recent advent of affordable wearable sensors has considerably expanded the range of these possibilities to fields such as computer gaming, education, entertainment, health, neuromarketing, psychology, etc. The Visual Attention Software by 3M (3M-VAS) is an artificial intelligence application that was formulated using experimental data from eye-tracking. It can be used to predict viewer reactions to images, generating fixation point probability maps and fixation point sequence estimations, thus revealing pre-attentive processing of visual stimuli with a very high degree of accuracy. We have used 3M-VAS software in an innovative implementation to analyze images of different buildings, either in their original state or photographically manipulated, as well as various geometric patterns. The software not only reveals non-obvious fixation points, but also overall relative design coherence, a key element of Christopher Alexander’s theory of geometrical order. A more evenly distributed field of attention seen in some structures contrasts with other buildings being ignored, those showing instead unconnected points of splintered attention. Our findings are non-intuitive and surprising. We link these results to both Alexander’s theory and Neuroscience, identify potential pitfalls in the software’s use, and also suggest ways to avoid them.

Sign in / Sign up

Export Citation Format

Share Document