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发明公开
CN109446878A 一种基于机器学习的视觉疲劳度检测方法 无效 - 驳回

一种基于机器学习的视觉疲劳度检测方法
摘要：
本发明公开了一种基于机器学习的视觉疲劳度检测方法。其包括以下步骤：在授课开始预定时间后，通过终端的摄像头获取学生的眼睛的巩膜血丝量；利用训练好的二元分类器对巩膜血丝量进行二元分类，确定学生的视觉疲劳度可信值；将授课时间作为权值，并根据权值对视觉疲劳度可信值进行加权滤波，得到视觉疲劳度真值；如果视觉疲劳度真值不高于预设异常阈值，则判定学生的眼睛不处于视觉疲劳状态，如果视觉疲劳度真值高于预设异常阈值，则判定学生的眼睛处于视觉疲劳状态。本发明能够在授课过程中检测学生的视觉疲劳度。
摘要（英）：

The invention discloses a visual fatigue degree detection method based on machine learning. The method comprises the following steps of obtaining the amount of scleral blood of the student's eye through the camera of the terminal after the teaching starts for a predetermined time; using the trained binary classifier to classify the scleral blood volume to determine the credible value of visual fatigue of the students; taking the teaching time as the weight value and weighting the credible value of visual fatigue degree according to the weight value to obtain the true value of visual fatigue degree; if the true value of the visual fatigue degree is not higher than the preset abnormal threshold value, judging that the eyes of the students are not in the visual fatigue state, and if the truevalue of the visual fatigue degree is higher than the preset abnormal threshold value, judging that the eyes of the students are in the visual fatigue state. The method of the invention can detect thevisual fatigue degree of the students in the teaching process.

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