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精细的眼部区域模型及其在面部图像分析中的应用。

Meticulously detailed eye region model and its application to analysis of facial images.

作者信息

Moriyama Tsuyoshi, Kanade Takeo, Xiao Jing, Cohn Jeffrey F

机构信息

Carnegie Mellon University, Pittsburgh, PA 15213-3890, USA.

出版信息

IEEE Trans Pattern Anal Mach Intell. 2006 May;28(5):738-52. doi: 10.1109/TPAMI.2006.98.

Abstract

We propose a system that is capable of detailed analysis of eye region images in terms of the position of the iris, degree of eyelid opening, and the shape, complexity, and texture of the eyelids. The system uses a generative eye region model that parameterizes the fine structure and motion of an eye. The structure parameters represent structural individuality of the eye, including the size and color of the iris, the width, boldness, and complexity of the eyelids, the width of the bulge below the eye, and the width of the illumination reflection on the bulge. The motion parameters represent movement of the eye, including the up-down position of the upper and lower eyelids and the 2D position of the iris. The system first registers the eye model to the input in a particular frame and individualizes it by adjusting the structure parameters. The system then tracks motion of the eye by estimating the motion parameters across the entire image sequence. Combined with image stabilization to compensate for appearance changes due to head motion, the system achieves accurate registration and motion recovery of eyes.

摘要

我们提出了一种能够根据虹膜位置、眼睑张开程度以及眼睑的形状、复杂度和纹理对眼部区域图像进行详细分析的系统。该系统使用一种生成式眼部区域模型,该模型对眼睛的精细结构和运动进行参数化。结构参数代表眼睛的结构个体性,包括虹膜的大小和颜色、眼睑的宽度、粗细和复杂度、眼睛下方凸起的宽度以及凸起上照明反射的宽度。运动参数代表眼睛的运动,包括上、下眼睑的上下位置以及虹膜的二维位置。该系统首先将眼睛模型注册到特定帧中的输入图像上,并通过调整结构参数使其个性化。然后,该系统通过估计整个图像序列中的运动参数来跟踪眼睛的运动。结合图像稳定技术以补偿由于头部运动引起的外观变化,该系统实现了眼睛的精确注册和运动恢复。

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