Feature matching and ArUco markers application in mobile eye tracking studies

Adam Bykowski, Szymon Kupiński
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引用次数: 2

Abstract

This paper presents eye tracking glasses data analysis automation techniques, utilizing image processing. Two separate techniques will be described. One method is used to automate mapping of point-of-regard to a static reference image using a feature matching algorithm AKAZE. The second method utilizes ArUco markers for mapping of point-of-regard to a screencast from a mobile device. The described methods are used to aggregate experiment statistical data for future analysis and presentation in forms like heatmaps or gaze plots. Algorithms are implemented in Python 3.6 and OpenCV library.
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特征匹配和ArUco标记在移动眼动追踪中的应用研究
本文介绍了眼动追踪眼镜数据分析自动化技术,利用图像处理。将描述两种不同的技术。一种方法是使用AKAZE特征匹配算法自动将关注点映射到静态参考图像。第二种方法利用ArUco标记将关注点映射到来自移动设备的屏幕截图。所描述的方法用于汇总实验统计数据,以便将来以热图或注视图等形式进行分析和呈现。算法在Python 3.6和OpenCV库中实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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