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| 插片式可穿戴眼球追踪系统 |
| Plug-in wearable eye-tracking system |
| 投稿时间：2023-03-09 |
| DOI：10.3969/j.issn.1005-5630.202303090049 |
| 中文关键词: 屈光不正 眼球追踪设备 眼动数据 瞳孔检测 眨眼检测 |
| 英文关键词:refractive error eye tracking device eye tracking data pupil detection blink detection |
| 基金项目:国家重点研发计划（2020YFB2007501） |
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| 中文摘要: |
| 针对不同屈光度人员使用穿戴式近眼眼球追踪设备无法自由更换镜片的问题，研发出一套插片式近眼眼球追踪系统设备。该系统是由近眼采集硬件平台和眼动特征提取算法两部分构成：硬件平台是根据插片验光试镜架结构设计的图像采集模块；眼动特征提取算法是通过机器学习训练眼睛检测器和眼部特征点检测器，再结合候选瞳孔拟合筛选策略得到瞳孔直径、中心点和眨眼频次。实验结果表明，系统算法中瞳孔检测正确率为97.24%，眨眼检测正确率为91.59%。该设备可满足屈光不正人群眼动追踪检测和研究的需求，同时提供准确可靠的眼动数据。 |
| 英文摘要: |
| Aiming at the problem that people with different diopters cannot freely change lenses when using wearable near-eye eye-tracking devices, this paper developed a set of plug-in near-eye eye-tracking system equipment. The system is composed of two parts: a near-eye acquisition hardware platform and an eye movement feature extraction algorithm. The hardware platform is an image acquisition module designed according to the structure of the optometry trial frame. The eye movement feature extraction algorithm is to train the eye detector and eye feature point detector based on machine learning, and then combines the candidate pupil fitting screening strategy to obtain the pupil diameter, center point, and blink frequency. The experimental results show that in this system algorithm, the correct rate of pupil detection is 97.24%, and the correct rate of blink detection is 91.59%. The device can meet the needs of eye-tracking detection and research for people with ametropia, and provide accurate and reliable eye-movement data. |
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