论文标题
大规模眼动仿真的平行眼动植物数学模型
Parallel Oculomotor Plant Mathematical Model for Large Scale Eye Movement Simulation
论文作者
论文摘要
预计眼睛跟踪传感器的使用将在虚拟（VR）和增强现实（AR）平台中增长。如果这些平台的用户同意使用被捕获的眼动信号进行身份验证和健康评估，那么实时估算动眼植物和大脑功能特征变得很重要。本文通过介绍能够估算动眼植物特征并将其性能与单线读取的实现进行比较的平行处理体系结构，展示了实现该目标的途径。结果表明，平行实现可提高动眼植物特征估计的速度，准确性和吞吐量与大规模和实时仿真的原始串行版本相比。
The usage of eye tracking sensors is expected to grow in virtual (VR) and augmented reality (AR) platforms. Provided that users of these platforms consent to employing captured eye movement signals for authentication and health assessment, it becomes important to estimate oculomotor plant and brain function characteristics in real time. This paper shows a path toward that goal by presenting a parallel processing architecture capable of estimating oculomotor plant characteristics and comparing its performance to a single-threaded implementation. Results show that the parallel implementation improves the speed, accuracy, and throughput of oculomotor plant characteristic estimation versus the original serial version for both large-scale and real-time simulation.
