Przeglądając różne blogi branżowe natrafiam od kilku miesięcy na temat webcam eye trackingu. Koncepcja ta opierająca się na wykorzystaniu zwykłych, istniejących w laptopach kamerek (webcam) do badań eyetrackingowych, na początku 2012 roku brzmi lekko absurdalnie. Ale być może za kilka lat, wraz z rozwojem technologii i spadkiem cen, może się rozwinie?
Aga Bojko, autorka mającej się ukazać w tym roku nakładem wydawnictwa Rosenfeld Media książki Eye Tracking the User Experience: A practical guide , popełniła bardzo interesujący wpis The Truth About Webcam Eye Tracking, w którym opisuje jak obecnie wygląda przeprowadzenie takiego badania i jakie są ich aktualne ograniczenia. Najważniejsze wnioski to:
- What decreases the accuracy of webcam eye tracking even further is when participants move their heads, and the longer the session, the more likely this will happen. Therefore, webcam eye tracking sessions have to be very short – typically less than 5 minutes, but ideally less than a minute. Studies conducted with real eye trackers, on the other hand, can last a lot longer with little impact on accuracy.
- Currently, webcam eye tracking can handle only single static pages. All four studies I have participated in and a few I read about were one-page studies. Without allowing participants to click on anything and go to another page, the applicability of webcam eye tracking is limited. This constraint also lowers the external validity of the studies.
- The rate at which the gaze location is sampled is much lower for webcams than real eye trackers. The typical frame rate of a remote (i.e., non-wearable) eye tracker is between 60 and 500 Hz (i.e., images per second). The webcam frame rate is somewhere between 5 and 30 Hz. The low frame rate makes analyzing fixations and saccades impossible. The analysis is limited to looking at rough gaze points.
- Due to imperfect lighting conditions, poor webcams, on-screen distractions, participants’ head movement, and overall lower tracking robustness, out of every 10 people who participate in a study, only 3 – 7 will provide sufficiently useful data. While this may not be a problem in and of itself because of very low oversampling costs, what makes me uncomfortable is not knowing how the determination to exclude data from the analysis is made. Data cleansing is important in any study but it is absolutely critical in webcam eye tracking. Exclusion criteria should be made explicit for webcam eye tracking to gain trust among researchers.
Źródło: The Truth About Webcam Eye Tracking, Aga Bojko, Rosenfeld Media Eye Tracking blog
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