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A Head Tracking Method for Improved Eye Movement Detection in Children

机译:一种用于改进儿童眼运动检测的头部跟踪方法

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The presence of untreated visual disorders in early childhood can result in abnormal visual cortex development (amblyopia). However, accurate clinical assessment of visual function in young children is highly challenging. Reflexive eye movements may allow for precise measurement of visual functions such as resolution acuity in young children if age appropriate, clinically acceptable, quantitative eye tracking techniques can be developed. Children do not tolerate chin-rests or head mounted eye-tracking equipment, therefore we have developed a method to measure and compensate for unrestrained head motion that may facilitate detection of eye movements. We implemented an automatic feature-based algorithm to track features on the face in pre-recorded videos. These data were used to "lock" the head to its initial position. Secondly, we implemented a single un-calibrated camera method to estimate the 3D movements of the head. The method was tested using video footage from five children who observed visual stimuli designed to induce horizontal optokinetic nystagmus (a reflexive sawtooth motion of the eye consisting of pursuit and saccadic eye movements). The children's heads were unrestrained, thereby exhibiting natural movement within the video. Markers placed on participants' faces were manually segmented to yield ground truth data. The standard deviation of head movement improved from (18.6676, 8.9088) to (1.8828,1.4282) pixels after stabilization. The average mean square error (MSE) between the manual and automatic stabilization methods was 7.7494 pixels. The percentage error for 3D pose estimation was 0.2428 %. Stabilization of the eyes (relative to the head) was achieved. In conclusion, our initial results suggest that head movement stabilization is possible as a post processing step which could significantly facilitate the monitoring of eye movements in children. Furthermore automated methods could improve the monitoring of neuro-developmental disorders that manifest through head movement.
机译:未处理的视觉障碍的儿童早期的存在可以导致异常的视觉皮层发展(弱视)。然而,在幼儿的视觉功能,准确的临床评估是非常具有挑战性的。自反眼球运动可允许的视觉功能,如在幼儿视力的分辨率精确的测量,如果适当的年龄,临床上可以接受的,定量的眼动追踪技术可开发。孩子不容忍下巴休息或头戴式眼球追踪设备,因此我们开发了测量和补偿可能有利于眼睛运动检测奔放的头部运动的方法。我们实施了一个自动的基于特征的算法来跟踪在脸上预先录制的视频功能。这些数据被用于“锁定”的头部到其初始位置。其次,我们实现来估计头部的三维运动的单一的未校准的相机的方法。该方法使用视频素材从谁观察设计用于诱导水平视动震颤(由追求和眼跳的眼睛的自反锯齿运动)的视觉刺激五个孩子测试。孩子们的头被奔放,从而显示在视频中的自然运动。放置在参与者的面部标记进行手工分割,以产生地面实况数据。头部运动的标准偏差从(18.6676,8.9088)提高到稳定后(1.8828,1.4282)的像素。手动和自动稳定方法之间的平均均方误差(MSE)为7.7494像素。三维姿态估计百分比误差为0.2428%。达到眼睛(相对于头部)的稳定。总之,我们的初步结果表明,头部运动的稳定是可能的后处理步骤,可以显著便于眼球运动在儿童中的监测。此外自动化方法可以改善神经发育障碍的表现是通过头部运动的监测。

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