双状态参数眼动追踪

Ying-li Tian, T. Kanade, J. Cohn
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引用次数: 189

摘要

大多数眼动仪在睁开眼睛时效果很好。然而,眨眼是人类的生理需要。此外,对于面部表情分析和驾驶员意识系统等应用,我们需要做的不仅仅是跟踪人的眼睛的位置,而是获得他们的详细描述。我们需要恢复眼睛的状态(即眼睛是开着还是闭着),以及眼睛模型的参数(例如虹膜的位置和半径,以及眼睛张开的角和高度)。我们开发了一个基于双状态模型的系统,用于跟踪眼睛特征,该系统使用收敛跟踪技术,并展示了如何使用它来检测眼睛是打开还是关闭,并恢复眼睛模型的参数。奔腾II 400 MHz PC的处理速度大约是3帧/秒。在对来自不同肤色和眼睛的儿童和成人受试者的500个图像序列进行实验测试中,98%的图像序列获得了准确的跟踪结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dual-state parametric eye tracking
Most eye trackers work well for open eyes. However blinking is a physiological necessity for humans. More over, for applications such as facial expression analysis and driver awareness systems, we need to do more than tracking of the locations of the person's eyes but obtain their detailed description. We need to recover the state of the eyes (i.e., whether they are open or closed), and the parameters of an eye model (e.g., the location and radius of the iris, and the corners and height of the eye opening). We develop a dual-state model-based system for tracking eye features that uses convergent tracking techniques and show how it can be used to detect whether the eyes are open or closed, and to recover the parameters of the eye model. Processing speed on a Pentium II 400 MHz PC is approximately 3 frames/second. In experimental tests on 500 image sequences from child and adult subjects with varying colors of skin and eye, accurate tracking results are obtained in 98% of image sequences.
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