| Title |
Online webcam-based eye tracking in cognitive science: A first look
|
|---|---|
| Published in |
Behavior Research Methods, June 2017
|
| DOI | 10.3758/s13428-017-0913-7 |
| Pubmed ID | |
| Authors |
Kilian Semmelmann, Sarah Weigelt |
| Abstract |
Online experimentation is emerging in many areas of cognitive psychology as a viable alternative or supplement to classical in-lab experimentation. While performance- and reaction-time-based paradigms are covered in recent studies, one instrument of cognitive psychology has not received much attention up to now: eye tracking. In this study, we used JavaScript-based eye tracking algorithms recently made available by Papoutsaki et al. (International Joint Conference on Artificial Intelligence, 2016) together with consumer-grade webcams to investigate the potential of online eye tracking to benefit from the common advantages of online data conduction. We compared three in-lab conducted tasks (fixation, pursuit, and free viewing) with online-acquired data to analyze the spatial precision in the first two, and replicability of well-known gazing patterns in the third task. Our results indicate that in-lab data exhibit an offset of about 172 px (15% of screen size, 3.94° visual angle) in the fixation task, while online data is slightly less accurate (18% of screen size, 207 px), and shows higher variance. The same results were found for the pursuit task with a constant offset during the stimulus movement (211 px in-lab, 216 px online). In the free-viewing task, we were able to replicate the high attention attribution to eyes (28.25%) compared to other key regions like the nose (9.71%) and mouth (4.00%). Overall, we found web technology-based eye tracking to be suitable for all three tasks and are confident that the required hard- and software will be improved continuously for even more sophisticated experimental paradigms in all of cognitive psychology. |
X Demographics
The data shown below were collected from the profiles of 29 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 10 | 34% |
| United Kingdom | 4 | 14% |
| Netherlands | 3 | 10% |
| Canada | 2 | 7% |
| Korea, Republic of | 1 | 3% |
| Curaçao | 1 | 3% |
| Unknown | 8 | 28% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 20 | 69% |
| Members of the public | 8 | 28% |
| Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 249 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 249 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 56 | 22% |
| Researcher | 35 | 14% |
| Student > Master | 21 | 8% |
| Student > Bachelor | 21 | 8% |
| Student > Doctoral Student | 15 | 6% |
| Other | 38 | 15% |
| Unknown | 63 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 56 | 22% |
| Computer Science | 22 | 9% |
| Neuroscience | 15 | 6% |
| Engineering | 11 | 4% |
| Medicine and Dentistry | 10 | 4% |
| Other | 56 | 22% |
| Unknown | 79 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 December 2020.
All research outputs
#2,131,502
of 25,382,440 outputs
Outputs from Behavior Research Methods
#220
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Outputs of similar age
#40,049
of 331,588 outputs
Outputs of similar age from Behavior Research Methods
#6
of 38 outputs
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