Trajectory prediction of saccadic eye movements using a compressed exponential model
Trajectory prediction of saccadic eye movements using a compressed exponential model
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DOI：
10.1167/13.8.27
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发表时间：
2013-01-01
影响因子：
1.8
通讯作者：
Luo, Gang
中科院分区：
文献类型：
--
作者：
Han, Peng;Saunders, Daniel R.;Luo, Gang
注视条件下的显示范式在视觉研究中起着重要作用。从眼动仪到监视器的数据传输的时间延迟可能导致眼动过程中注视方向和图像操作的不一致，从而影响偶然性。我们提出了一种方法，通过使用压缩指数函数来模拟跳眼运动的轨迹来减少这种不对齐。使用EyeLink 1000和双浦肯野图像（Dual-Purkinje Image， DPI）眼动仪收集的1212次3度至30度的扫视数据对算法进行了评估。模型对眼位移的拟合度较高（R-2 > 0.96）。当假设10毫秒的时间延迟时，使用我们的模型预测二维扫视轨迹，对于大于8度的扫视，使用EyeLink跟踪器可以减少30%到60%的不对准，使用DPI跟踪器可以减少20%到40%的不对准。由于模型拟合需要一定数量的样本，该预测对大多数小扫视和大扫视的早期阶段没有提供改善。使用预先记录的跳频数据，还对模拟的100 hz凝视随机显示进行了评估。通过预测，大于2度的偏差百分比在EyeLink数据中从45%下降到20%，在DPI数据中从42%下降到26%。这些结果表明，眼跳预测算法可能有助于创建更准确的注视显示。
Gaze-contingent display paradigms play an important role in vision research. The time delay due to data transmission from eye tracker to monitor may lead to a misalignment between the gaze direction and image manipulation during eye movements, and therefore compromise the contingency. We present a method to reduce this misalignment by using a compressed exponential function to model the trajectories of saccadic eye movements. Our algorithm was evaluated using experimental data from 1,212 saccades ranging from 3 degrees to 30 degrees, which were collected with an EyeLink 1000 and a Dual-Purkinje Image (DPI) eye tracker. The model fits eye displacement with a high agreement (R-2 > 0.96). When assuming a 10-millisecond time delay, prediction of 2D saccade trajectories using our model could reduce the misalignment by 30% to 60% with the EyeLink tracker and 20% to 40% with the DPI tracker for saccades larger than 8 degrees. Because a certain number of samples are required for model fitting, the prediction did not offer improvement for most small saccades and the early stages of large saccades. Evaluation was also performed for a simulated 100-Hz gaze-contingent display using the prerecorded saccade data. With prediction, the percentage of misalignment larger than 2 degrees dropped from 45% to 20% for EyeLink and 42% to 26% for DPI data. These results suggest that the saccade-prediction algorithm may help create more accurate gaze-contingent displays.