Veriye Dayalı Yinelemeli-Uyarlamalı Algoritma Kullanılarak VR’da Göz İzleme Metriklerinin Tanımlanması

Öz

Göz izleme ölçümleri, bilişsel işlev ve temel okülomotor özellikler hakkında bilgi sağlar. Farklı algoritmalar kullanarak göz izleme sinyallerini analiz eden birçok çalışma yapılmıştır. Ancak bu algoritmalar genellikle ilk ayar parametresine dayalıdır. Bu, göz izleme analizinin öznel yorumuna neden olabilir. Bu çalışmanın temel amacı, herhangi bir öznel ayar olmaksızın fiksasyonları ve sakkadları tespit etmek için veriye dayalı bir algoritma geliştirmekti. Bu çalışmaya üç konu dahil edilmiştir. Denekler VR'de bir paragraf okurken, sanal gerceklik (VR) ortamında VIVE Pro Eye ile göz izleme sinyali alındı. Toplam sabitleme süresi, toplam sabitleme sayısı, toplam sakkad sayısı ve ortalama göz bebeği çapı dahil olmak üzere göz ölçümlerini hesaplamak için eşiğin hesaplanmasına dayalı algoritmalar kullanıldı. Deney süresi içinde göz izleme sinyalinin ortalama ve standart sapmasına bağlı olarak başlangıç eşiğini hesaplamaya dayanan önerilen algoritma, literatürde bildirilen uyarlamalı filtreleme ile elde edilen sonuçların aynısını vermiştir (üç denek için ortalama fiksasyon süresi= 11515 ms ± 6951.2, üç denek için ortalama fiksasyon sayısı= 17.33 ± 4.16). Öte yandan, önerilen algoritmamız uyarlamalı filtreleme gibi belirli bir nesnel parametre kullanmamıştır. Sonuç olarak, VIVE Pro Eye bir göz hareketi değerlendirme cihazı olarak kullanılabilir ve önerilen yaklaşım objektif göz izleme metriklerini analiz etmek için kullanılabilir.

Anahtar Kelimeler

• göz izleme
• sanal gerçeklik
• fiksasyon
• sakkad
• başa monte ekran

The Identification of Individualized Eye Tracking Metrics in VR Using Data Driven Iterative- Adaptive Algorithm

Öz

Eye tracking metrics provide information about cognitive function and basic oculomotor characteristics. There have been many studies analyzing eye tracking signals using different algorithms. However, these algorithms generally are based on the initial setting parameter. This might cause the subjective interpretation of eye tracking analysis. The main aim of this study was to develop a data-driven algorithm to detect fixations and saccades without any subjective settings. Three subjects were included in this study. Eye tracking signal was acquired with the VIVE Pro Eye in virtual reality (VR) environment while subjects were reading a paragraph. The algorithms based on the calculation of threshold were employed to calculate eye metrics including total fixation duration, total fixation number, total saccades number and average pupil diameter. The proposed algorithm, which is based on calculating the initial threshold, based on mean, and standard deviation of eye tracking signal within experiment duration, gave the same results obtained adaptive filtering reported in literature (average fixation duration for three subjects= 11515 ms ± 6951.2, average fixation count for three subjects= 17.33 ± 4.16). On the other hand, our proposed algorithm didn’t use any certain objective parameter as like adaptive filtering. As a conclusion, VIVE Pro Eye may be utilized as an eye movement assessment device, and, the suggested approach might be utilized to analyze objective eye tracking metrics.

Anahtar Kelimeler

• eye tracking
• virtual reality
• head mounted display
• saccade
• fixation

Kaynakça

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