Abstract
Fixation identification is an essential task in the extraction of relevant information from gaze patterns; various algorithms are used in the identification process. However, the thresholds used in the algorithms greatly affect their sensitivity. Moreover, the application of these algorithm to eye-tracking technologies integrated into head-mounted displays, where the subject’s head position is unrestricted, is still an open issue. Therefore, the adaptation of eye-tracking algorithms and their thresholds to immersive virtual reality frameworks needs to be validated. This study presents the development of a dispersion-threshold identification algorithm applied to data obtained from an eye-tracking system integrated into a head-mounted display. Rules-based criteria are proposed to calibrate the thresholds of the algorithm through different features, such as number of fixations and the percentage of points which belong to a fixation. The results show that distance-dispersion thresholds between 1–1.6° and time windows between s are the acceptable range parameters, with 1° and s being the optimum. The work presents a calibrated algorithm to be applied in future experiments with eye-tracking integrated into head-mounted displays and guidelines for calibrating fixation identification algorithms
Highlights
Virtual Reality (VR) is a rapidly improving emerging technology [1]
The algorithm presented is robust in the face of these fluctuations, and rejects possible fixation classifications for points below a certain frequency threshold
The present study has demonstrated the implications of using an I-DT algorithm in an Immersive virtual environments (IVE), which includes some key points as the head movement of the subjects, previously presented by Reference [30]
Summary
Virtual Reality (VR) is a rapidly improving emerging technology [1]. VR allows the simulation of experiences which create the sensation of being in the real world [2]. It is very helpful in human-subject-based experiments that are difficult to perform in the real world; it offers environment simulations under controlled laboratory conditions where researchers can efficiently isolate and manipulate features while keeping the other environmental stimuli unchanged [3,4]. VR allows free navigation and real-world type movement [5], it can evoke similar emotions and cognitive process to physical environments [6,7].
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