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Joint iris boundary detection and fit: a real-time method for accurate pupil tracking

机译:联合虹膜边界检测和拟合:用于精确瞳孔跟踪的实时方法

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摘要

A range of applications in visual science rely on accurate tracking of the human pupil’s movement and contraction in response to light. While the literature for independent contour detection and fitting of the iris-pupil boundary is vast, a joint approach, in which it is assumed that the pupil has a given geometric shape has been largely overlooked. We present here a global method for simultaneously finding and fitting of an elliptic or circular contour against a dark interior, which produces consistently accurate results even under non-ideal recording conditions, such as reflections near and over the boundary, droopy eye lids, or the sudden formation of tears. The specific form of the proposed optimization problem allows us to write down closed analytic formulae for the gradient and the Hessian of the objective function. Moreover, both the objective function and its derivatives can be cast into vectorized form, making the proposed algorithm significantly faster than its closest relative in the literature. We compare methods in multiple ways, both analytically and numerically, using real iris images as well as idealizations of the iris for which the ground truth boundary is precisely known. The method proposed here is illustrated under challenging recording conditions and it is shown to be robust.
机译:视觉科学的各种应用都依赖于对人类学生对光的运动和收缩的精确跟踪。尽管有关虹膜瞳孔边界的独立轮廓检测和拟合的文献非常丰富,但在很大程度上却忽略了一种联合方法,其中假定瞳孔具有给定的几何形状。我们在这里介绍了一种同时针对黑暗的内部同时查找和拟合椭圆或圆形轮廓的全局方法,即使在非理想的记录条件下(例如边界附近和上方的反射,下垂的眼睑或下垂的反射),该方法也能产生一致准确的结果。突然形成眼泪。所提出的优化问题的特定形式使我们能够为目标函数的梯度和Hessian写下封闭的解析公式。而且,目标函数及其导数都可以转换为矢量化形式,从而使该算法比文献中最接近的算法快得多。我们使用真实的虹膜图像以及精确地知道地面真实边界的虹膜的理想化,以多种方式在分析和数值上比较方法。此处提出的方法在具有挑战性的记录条件下进行了说明,并且显示了鲁棒性。

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