A Ground-Truth Data Set and a Classification Algorithm for Eye Movements in 360-degree Videos

Abstract

The segmentation of a gaze trace into its constituent eye movements has been actively researched since the early days of eye tracking. As we move towards more naturalistic viewing conditions, the segmentation becomes even more challenging and convoluted as more complex patterns emerge. The definitions and the well-established methods that were developed for monitor-based eye tracking experiments are often not directly applicable to unrestrained set-ups such as eye tracking in wearable contexts or with head-mounted displays. The main contributions of this work to the eye movement research for 360 • content are threefold: First, we collect, partially annotate, and make publicly available a new eye tracking data set, which consists of 13 participants viewing 15 video clips that are recorded in 360 • . Second, we propose a new two-stage pipeline for ground truth annotation of the traditional fixations, saccades, smooth pursuits, as well as (optokinetic) nystagmus, vestibuloocular reflex, and pursuit of moving objects performed exclusively via the movement of the head. A flexible user interface for this pipeline is implemented and made freely accessible for use or modification. Lastly, we develop and test a simple proof-of-concept algorithm for automatic classification of all the eye movement types in our data set based on their operational definitions that were used for manual annotation. The data set and the source code for both the annotation tool and the algorithm are publicly available at https://web.gin.g-node.org/ioannis.agtzidis/360_em_dataset.

Evaluating the Difference in Gaze Patterns for 360° Video-Based and 3D Modeled Virtual Environments

“…Together, xations and saccades create the overall pattern of the gaze scan path (Kübler et al 2014;Geisler et al 2020). Detecting those events can be achieved through a probabilistic, velocity, or duration threshold-setting approach (Salvucci and Goldberg 2000;Tafaj et al 2012;Santini et al 2016;Agtzidis et al 2019).…”

“…Salvucci and Goldberg 2000;Agtzidis et al 2019). Table8depicts the duration (∆) and velocity ( ) thresholds used to determine eye-movement events similar to the approach applied by Agtzidis et al (2019) andGao et al (2021).…”