scholarly journals EVALUATION OF COLOR SETTINGS IN AERIAL IMAGES WITH THE USE OF EYE-TRACKING USER STUDY

2016 ◽  
Vol XLI-B3 ◽  
pp. 763-767
Author(s):  
J. Mirijovsky ◽  
S. Popelka
Keyword(s):  
Eye Tracking ◽  
User Study ◽  
Aerial Images ◽  
Eye Tracker ◽  
Lighting Conditions ◽  
Graphic Editor ◽  
Real Value ◽  
Crop Area ◽  
Different Color ◽  
Areas Of Interest

The main aim of presented paper is to find the most realistic and preferred color settings for four different types of surfaces on the aerial images. This will be achieved through user study with the use of eye-movement recording. Aerial images taken by the unmanned aerial system were used as stimuli. From each image, squared crop area containing one of the studied types of surfaces (asphalt, concrete, water, soil, and grass) was selected. For each type of surface, the real value of reflectance was found with the use of precise spectroradiometer ASD HandHeld 2 which measures the reflectance. The device was used at the same time as aerial images were captured, so lighting conditions and state of vegetation were equal. The spectral resolution of the ASD device is better than 3.0 nm. For defining the RGB values of selected type of surface, the spectral reflectance values recorded by the device were merged into wider groups. Finally, we get three groups corresponding to RGB color system. Captured images were edited with the graphic editor Photoshop CS6. Contrast, clarity, and brightness were edited for all surface types on images. Finally, we get a set of 12 images of the same area with different color settings. These images were put into the grid and used as stimuli for the eye-tracking experiment. Eye-tracking is one of the methods of usability studies and it is considered as relatively objective. Eye-tracker SMI RED 250 with the sampling frequency 250 Hz was used in the study. As respondents, a group of 24 students of Geoinformatics and Geography was used. Their task was to select which image in the grid has the best color settings. The next task was to select which color settings they prefer. Respondents’ answers were evaluated and the most realistic and most preferable color settings were found. The advantage of the eye-tracking evaluation was that also the process of the selection of the answers was analyzed. Areas of Interest were marked around each image in the grid and the sequences of gaze movements were analyzed. Sequence chart was used for visualization and eye-tracking metrics were statistically tested. The presented paper shows the differences in the perception and preferences of aerial images with different color settings.

scholarly journals EVALUATION OF COLOR SETTINGS IN AERIAL IMAGES WITH THE USE OF EYE-TRACKING USER STUDY

2016 ◽  
Vol XLI-B3 ◽  
pp. 763-767 ◽  
Author(s):  
J. Mirijovsky ◽  
S. Popelka
Keyword(s):  
Eye Tracking ◽  
User Study ◽  
Aerial Images ◽  
Eye Tracker ◽  
Lighting Conditions ◽  
Graphic Editor ◽  
Real Value ◽  
Crop Area ◽  
Different Color ◽  
Areas Of Interest

The main aim of presented paper is to find the most realistic and preferred color settings for four different types of surfaces on the aerial images. This will be achieved through user study with the use of eye-movement recording. Aerial images taken by the unmanned aerial system were used as stimuli. From each image, squared crop area containing one of the studied types of surfaces (asphalt, concrete, water, soil, and grass) was selected. For each type of surface, the real value of reflectance was found with the use of precise spectroradiometer ASD HandHeld 2 which measures the reflectance. The device was used at the same time as aerial images were captured, so lighting conditions and state of vegetation were equal. The spectral resolution of the ASD device is better than 3.0 nm. For defining the RGB values of selected type of surface, the spectral reflectance values recorded by the device were merged into wider groups. Finally, we get three groups corresponding to RGB color system. Captured images were edited with the graphic editor Photoshop CS6. Contrast, clarity, and brightness were edited for all surface types on images. Finally, we get a set of 12 images of the same area with different color settings. These images were put into the grid and used as stimuli for the eye-tracking experiment. Eye-tracking is one of the methods of usability studies and it is considered as relatively objective. Eye-tracker SMI RED 250 with the sampling frequency 250 Hz was used in the study. As respondents, a group of 24 students of Geoinformatics and Geography was used. Their task was to select which image in the grid has the best color settings. The next task was to select which color settings they prefer. Respondents’ answers were evaluated and the most realistic and most preferable color settings were found. The advantage of the eye-tracking evaluation was that also the process of the selection of the answers was analyzed. Areas of Interest were marked around each image in the grid and the sequences of gaze movements were analyzed. Sequence chart was used for visualization and eye-tracking metrics were statistically tested. The presented paper shows the differences in the perception and preferences of aerial images with different color settings.

The Use of Eye Tracking to Discern the Threshold at Which Metopic Orbitofrontal Deformity Attracts Attention

2020 ◽  
Vol 57 (12) ◽  
pp. 1392-1401
Author(s):  
Mark P. Pressler ◽  
Emily L. Geisler ◽  
Rami R. Hallac ◽  
James R. Seaward ◽  
Alex A. Kane
Keyword(s):  
Surgical Treatment ◽  
Graduate Students ◽  
Eye Tracking ◽  
Dwell Time ◽  
Surgical Intervention ◽  
Three Dimensional ◽  
Average Dwell Time ◽  
Eye Tracker ◽  
Gaze Patterns ◽  
Areas Of Interest

Introduction and Objectives: Surgical treatment for trigonocephaly aims to eliminate a stigmatizing deformity, yet the severity that captures unwanted attention is unknown. Surgeons intervene at different points of severity, eliciting controversy. This study used eye tracking to investigate when deformity is perceived. Material and Methods: Three-dimensional photogrammetric images of a normal child and a child with trigonocephaly were mathematically deformed, in 10% increments, to create a spectrum of 11 images. These images were shown to participants using an eye tracker. Participants’ gaze patterns were analyzed, and participants were asked if each image looked “normal” or “abnormal.” Results: Sixty-six graduate students were recruited. Average dwell time toward pathologic areas of interest (AOIs) increased proportionally, from 0.77 ± 0.33 seconds at 0% deformity to 1.08 ± 0.75 seconds at 100% deformity ( P < .0001). A majority of participants did not agree an image looked “abnormal” until 90% deformity from any angle. Conclusion: Eye tracking can be used as a proxy for attention threshold toward orbitofrontal deformity. The amount of attention toward orbitofrontal AOIs increased proportionally with severity. Participants did not generally agree there was “abnormality” until deformity was severe. This study supports the assertion that surgical intervention may be best reserved for more severe deformity.

scholarly journals Use of Eye-Tracking Technology by Medical Students Taking the Objective Structured Clinical Examination: Descriptive Study

10.2196/17719 ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. e17719
Author(s):  
M D Grima-Murcia ◽  
Francisco Sanchez-Ferrer ◽  
Jose Manuel Ramos-Rincón ◽  
Eduardo Fernández
Keyword(s):  
Medical Students ◽  
Eye Tracking ◽  
Clinical Examination ◽  
Objective Evaluation ◽  
Objective Structured Clinical Examination ◽  
Eye Tracker ◽  
Clinical Competencies ◽  
Self Evaluation ◽  
Areas Of Interest ◽  
Tracking Technology

Background The objective structured clinical examination (OSCE) is a test used throughout Spain to evaluate the clinical competencies, decision making, problem solving, and other skills of sixth-year medical students. Objective The main goal of this study is to explore the possible applications and utility of portable eye-tracking systems in the setting of the OSCE, particularly questions associated with attention and engagement. Methods We used a portable Tobii Glasses 2 eye tracker, which allows real-time monitoring of where the students were looking and records the voice and ambient sounds. We then performed a qualitative and a quantitative analysis of the fields of vision and gaze points attracting attention as well as the visual itinerary. Results Eye-tracking technology was used in the OSCE with no major issues. This portable system was of the greatest value in the patient simulators and mannequin stations, where interaction with the simulated patient or areas of interest in the mannequin can be quantified. This technology proved useful to better identify the areas of interest in the medical images provided. Conclusions Portable eye trackers offer the opportunity to improve the objective evaluation of candidates and the self-evaluation of the stations used as well as medical simulations by examiners. We suggest that this technology has enough resolution to identify where a student is looking at and could be useful for developing new approaches for evaluating specific aspects of clinical competencies.

scholarly journals Computer-generated facial areas of interest in eye tracking research: A simulation study

2021 ◽  
Author(s):  
Antonia Vehlen ◽  
William Standard ◽  
Gregor Domes
Keyword(s):  
Eye Tracking ◽  
Voronoi Tessellation ◽  
Data Accuracy ◽  
Type I ◽  
Type Ii ◽  
Eye Tracker ◽  
Type I Errors ◽  
Areas Of Interest ◽  
Type Ii Errors ◽  
The Impact

Advances in eye tracking technology have enabled the development of interactive experimental setups to study social attention. Since these setups differ substantially from the eye tracker manufacturer’s test conditions, validation is essential with regard to data quality and other factors potentially threatening data validity. In this study, we evaluated the impact of data accuracy and areas of interest (AOIs) size on the classification of simulated gaze data. We defined AOIs of different sizes using the Limited-Radius Voronoi-Tessellation (LRVT) method, and simulated gaze data for facial target points with varying data accuracy. As hypothesized, we found that data accuracy and AOI size had strong effects on gaze classification. In addition, these effects were not independent and differed for falsely classified gaze inside AOIs (Type I errors) and falsely classified gaze outside the predefined AOIs (Type II errors). The results indicate that smaller AOIs generally minimize false classifications as long as data accuracy is good enough. For studies with lower data accuracy, Type II errors can still be compensated to some extent by using larger AOIs, but at the cost of an increased probability of Type I errors. Proper estimation of data accuracy is therefore essential for making informed decisions regarding the size of AOIs.

scholarly journals Use of Eye-Tracking Technology by Medical Students Taking the Objective Structured Clinical Examination: Descriptive Study (Preprint)

2020 ◽  
Author(s):  
M D Grima-Murcia ◽  
Francisco Sanchez-Ferrer ◽  
Jose Manuel Ramos-Rincón ◽  
Eduardo Fernández
Keyword(s):  
Medical Students ◽  
Eye Tracking ◽  
Clinical Examination ◽  
Objective Evaluation ◽  
Objective Structured Clinical Examination ◽  
Eye Tracker ◽  
Clinical Competencies ◽  
Self Evaluation ◽  
Areas Of Interest ◽  
Tracking Technology

BACKGROUND The objective structured clinical examination (OSCE) is a test used throughout Spain to evaluate the clinical competencies, decision making, problem solving, and other skills of sixth-year medical students. OBJECTIVE The main goal of this study is to explore the possible applications and utility of portable eye-tracking systems in the setting of the OSCE, particularly questions associated with attention and engagement. METHODS We used a portable Tobii Glasses 2 eye tracker, which allows real-time monitoring of where the students were looking and records the voice and ambient sounds. We then performed a qualitative and a quantitative analysis of the fields of vision and gaze points attracting attention as well as the visual itinerary. RESULTS Eye-tracking technology was used in the OSCE with no major issues. This portable system was of the greatest value in the patient simulators and mannequin stations, where interaction with the simulated patient or areas of interest in the mannequin can be quantified. This technology proved useful to better identify the areas of interest in the medical images provided. CONCLUSIONS Portable eye trackers offer the opportunity to improve the objective evaluation of candidates and the self-evaluation of the stations used as well as medical simulations by examiners. We suggest that this technology has enough resolution to identify where a student is looking at and could be useful for developing new approaches for evaluating specific aspects of clinical competencies.

scholarly journals Emotional Expression Processing and Depressive Symptomatology: Eye-Tracking Reveals Differential Importance of Lower and Middle Facial Areas of Interest

2020 ◽  
Vol 2020 ◽  
pp. 1-7 ◽  
Author(s):  
Laurie Hunter ◽  
Laralin Roland ◽  
Ayesha Ferozpuri
Keyword(s):  
Depressive Symptoms ◽  
Eye Tracking ◽  
Depressive Symptomatology ◽  
Emotional Expressions ◽  
Eye Tracker ◽  
Area Of Interest ◽  
Visit Duration ◽  
The Face ◽  
Areas Of Interest ◽  
Expression Processing

The current study explored the eye-tracking patterns of individuals with nonclinical levels of depressive symptomatology when processing emotional expressions. Fifty-three college undergraduates were asked to label 80 facial expressions of five emotions (anger, fear, happiness, neutral, and sadness) while an eye-tracker measured visit duration. We argue visit duration provides more detailed information for evaluating which features of the face are used more often for processing emotional faces. Our findings indicated individuals with nonclinical levels of depressive symptomatology process emotional expressions very similarly to individuals with little to no depressive symptoms, with one noteworthy exception. In general, individuals in our study visited the “T” region, lower and middle AOIs (Area of Interest), more often than upper and noncore areas, but the distinction between the lower and middle AOIs appears for happiness only when individuals are higher in depressive symptoms.

scholarly journals Eye tracking metrics and leader’s behavioral performance during a post-partum hemorrhage high-fidelity simulated scenario

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Emanuele Capogna ◽  
Giorgio Capogna ◽  
Denise Raccis ◽  
Francesco Salvi ◽  
Matteo Velardo ◽  
...  
Keyword(s):  
Eye Tracking ◽  
Team Performance ◽  
Postpartum Hemorrhage ◽  
Post Partum ◽  
Eye Contact ◽  
Assessment Process ◽  
High Fidelity ◽  
Eye Tracker ◽  
Sources Of Information ◽  
Areas Of Interest

Abstract Background The use of eye tracking in the simulated setting can help improve our understanding of what sources of information clinicians are using as they deliver routine patient care. The aim of this simulation study was to observe the differences, if any, between the eye tracking patterns of leaders who performed best in a simulated postpartum hemorrhage (PPH) high-fidelity scenario, in comparison with those who performed worst. Methods Forty anesthesia trainees from the University of Catania Medical School were divided into eight teams, to enact four times the same scenario of a patient with postpartum hemorrhage following vaginal delivery. Trainees who were assigned the leader’s role wore the eye tracking glasses during the scenario, and their behavioral skills were evaluated by two observers, who reviewed the video recordings of the scenarios using a standardized checklist. The leader’s eye tracking metrics, extracted from 27 selected areas of interest (AOI), were recorded by a Tobii Pro Glasses 50 Hz wearable wireless eye tracker. Team performance was evaluated using a PPH checklist. After completion of the study, the leaders were divided into two groups, based on the scores they had received (High-Performance Leader group, HPL, and Low-Performance Leader group, LPL). Results In the HPL group, the duration and number of fixations were greater, and the distribution of gaze was uniformly distributed among the various members of the team as compared with the LPL group (with the exception of the participant who performed the role of the obstetrician). The HPL group also looked both at the patient’s face and established eye contact with their team members more often and for longer (P < .05). The team performance (PPH checklist) score was greater in the HPL group (P < .001). The LPL group had more and/or longer fixations of technical areas of interest (P < .05). Conclusions Our findings suggest that the leaders who perform the best distribute their gaze across all members of their team and establish direct eye contact. They also look longer at the patient’s face and dwell less on areas that are more relevant to technical skills. In addition, the teams led by these best performing leaders fulfilled their clinical task better. The information provided by the eye behaviors of “better-performing physicians” may lay the foundation for the future development of both the assessment process and the educational tools used in simulation. Trial Registration Clinical.Trial.Gov ID n. NCT04395963.

scholarly journals Look before you Authorize: Using Eye-Tracking to Enforce User Attention towards Application Permissions

2017 ◽  
Vol 2017 (2) ◽  
pp. 23-37 ◽  
Author(s):  
Yousra Javed ◽  
Mohamed Shehab
Keyword(s):  
Eye Tracking ◽  
User Study ◽  
Eye Gaze ◽  
Third Party ◽  
Security And Privacy ◽  
Control Group ◽  
Eye Tracker ◽  
Key Factor ◽  
User Attention ◽  
Gaze Fixations

Abstract Habituation is a key factor behind the lack of attention towards permission authorization dialogs during third party application installation. Various solutions have been proposed to combat the problem of achieving attention switch towards permissions. However, users continue to ignore these dialogs, and authorize dangerous permissions, which leads to security and privacy breaches. We leverage eye-tracking to approach this problem, and propose a mechanism for enforcing user attention towards application permissions before users are able to authorize them. We deactivate the dialog’s decision buttons initially, and use feedback from the eye-tracker to ensure that the user has looked at the permissions. After determining user attention, the buttons are activated. We implemented a prototype of our approach as a Chrome browser extension, and conducted a user study on Facebook’s application authorization dialogs. Using participants’ permission identification, eye-gaze fixations, and authorization decisions, we evaluate participants’ attention towards permissions. The participants who used our approach on authorization dialogs were able to identify the permissions better, compared to the rest of the participants, even after the habituation period. Their average number of eye-gaze fixations on the permission text was significantly higher than the other group participants. However, examining the rate in which participants denied a dangerous and unnecessary permission, the hypothesized increase from the control group to the treatment group was not statistically significant.

scholarly journals A Quality-Centered Analysis of Eye Tracking Data in Foveated Rendering

2017 ◽  
Vol 10 (5) ◽  
Author(s):  
Thorsten Roth ◽  
Martin Weier ◽  
André Hinkenjann ◽  
Yongmin Li ◽  
Philipp Slusallek
Keyword(s):  
Eye Tracking ◽  
User Study ◽  
Image Synthesis ◽  
Synthesis Process ◽  
Eye Tracker ◽  
Quality Ratings ◽  
Interesting Connection ◽  
Head Mounted Displays ◽  
High Level ◽  
Tracking Device

This work presents the analysis of data recorded by an eye tracking device in the course of evaluating a foveated rendering approach for head-mounted displays (HMDs). Foveated ren- dering methods adapt the image synthesis process to the user’s gaze and exploiting the human visual system’s limitations to increase rendering performance. Especially, foveated rendering has great potential when certain requirements have to be fulfilled, like low-latency rendering to cope with high display refresh rates. This is crucial for virtual reality (VR), as a high level of immersion, which can only be achieved with high rendering performance and also helps to reduce nausea, is an important factor in this field. We put things in context by first providing basic information about our rendering system, followed by a description of the user study and the collected data. This data stems from fixation tasks that subjects had to perform while being shown fly-through sequences of virtual scenes on an HMD. These fixation tasks consisted of a combination of various scenes and fixation modes. Besides static fixation targets, moving tar- gets on randomized paths as well as a free focus mode were tested. Using this data, we estimate the precision of the utilized eye tracker and analyze the participants’ accuracy in focusing the displayed fixation targets. Here, we also take a look at eccentricity-dependent quality ratings. Comparing this information with the users’ quality ratings given for the displayed sequences then reveals an interesting connection between fixation modes, fixation accuracy and quality ratings.

scholarly journals GazeR: A Package for Processing Gaze Position and Pupil Size Data

2019 ◽  
Author(s):  
Jason Geller ◽  
Matthew Winn ◽  
Tristan Mahr ◽  
Daniel Mirman
Keyword(s):  
Eye Tracking ◽  
Pupil Size ◽  
Programming Environment ◽  
Eye Tracker ◽  
Vision Science ◽  
Position Data ◽  
Statistical Programming ◽  
Data Files ◽  
Areas Of Interest ◽  
Gaze Position

Eye-tracking is widely used throughout the scientific community, from vision science and psycholinguistics, to marketing and human-computer interaction. Surprisingly, there is little consistency and transparency in preprocessing steps, making replicability difficult. To increase replicability and transparency, a package in R (a free and widely used statistical programming environment) called gazeR was created to read in and preprocess two types of data from the SR EyeLink eye tracker: gaze position and pupil size. For gaze position data, gazeR has functions for: reading in raw eye-tracking data, formatting it for analysis, converting from gaze coordinates to areas of interest, and binning and aggregating data. For data from pupillometry studies, the gazeR package has functions for: reading in and merging multiple raw pupil data files, removing observations with too much missing data, eliminating artifacts, blink identification and interpolation, subtractive baseline correction, and binning and aggregating data. The package is open-source and freely available for download and installation: https://github.com/dmirman/gazer. We provide step

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