The eye tracking technology is used for four decades for studying reading behavior. The applications are various: estimating the reader comprehension, identifying the reader, summarizing a read document, creating a reading-life log, etc. The gaze data used in such applications has to be accurate enough to perform the analysis. In order to improve the accuracy, most of the experiments are set up with restrictive conditions such as using a head fixation and a professional eye tracker. It implies that the results are valid only in restrictive laboratory settings and an unrealistic small error is produced by the experiment. However, the use of affordable eye trackers in realistic conditions of reading leads to large errors in the recordings. We propose a new algorithm to correct the vertical error and to align the gazes with the text. The proposed algorithm is robust to rereading and skipping some parts of text, contrary to all the other algorithms of the state of the art. We show that up to 69 % of the gazes are aligned with the correct text lines.

中文翻译：

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非限制性阅读条件下眼动仪的垂直误差校正

眼动追踪技术用于研究阅读行为已有四十年的时间。这些应用程序有多种：估算读者的理解力，识别读者，汇总已阅读的文档，创建阅读寿命日志等。此类应用程序中使用的凝视数据必须足够准确才能执行分析。为了提高准确性，大多数实验都是在限制性条件下进行的，例如使用头部固定装置和专业的眼动仪。这意味着结果仅在限制性实验室设置中有效，并且实验产生了不切实际的小错误。但是，在现实的阅读条件下使用价格适中的眼动仪会导致录音中的错误。我们提出了一种新的算法来纠正垂直误差并将视线与文本对齐。与现有技术的所有其他算法相反，所提出的算法对于重新读取和跳过文本的某些部分具有鲁棒性。我们显示多达69％的注视与正确的文本行对齐。