基于约束视觉拟合的鲁棒虹膜定位与跟踪

C. Colombo, Dario Comanducci, A. Bimbo
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引用次数: 5

摘要

提出了一种基于计算机视觉的鲁棒虹膜定位与跟踪算法。虹膜定位算法充当跟踪算法的引导器,为跟踪算法提供一组多个假设,以便在跟踪失败的情况下重新启动。采用一种类似RANSAC的鲁棒椭圆拟合方法进行跟踪,该方法结合了搜索约束,从而提高了相对于标准RANSAC方法的整体精度。实验结果表明,该算法速度快、精度高、鲁棒性好,适合于人机交互领域的应用,特别适合于有严重运动障碍的用户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Iris Localization and Tracking based on Constrained Visual Fitting
A robust iris localization and tracking algorithm based on computer vision is presented. The iris localization algorithm acts as a bootstrap for the tracking algorithm, providing it with a set of multiple hypotheses to restart from in the case of a tracking failure. Tracking is performed with a RANSAC-like robust method for ellipse fitting that incorporates search constraints so as to increase the overall accuracy with respect to the standard RANSAC approach. Experimental results show that the algorithm is fast, accurate and robust enough for applications in the field of human-machine interaction, being particularly suitable for users with severe motor disabilities.
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