The influence of calibration method and eye physiology on eyetracking data quality

By Marcus Nyström, Richard Andersson, Kenneth Holmqvist, Joost van de Weijer. Behavior Research Methods, 2012

300 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Ophthalmology, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/cf664479880e685bedfb372818260e19ea81cbb2

Citations in the corpus

• Consequences of eye color, positioning, and head movement for eye-tracking data quality in infant research (2015, unknown): “Data loss, the final aspect of data quality, refers to the proportion of valid samples that the eye tracker reports (Nystr € om et al., 2013).”