Specular Highlight Removal in Facial Images

Chen Li, Stephen Lin, Kun Zhou, K. Ikeuchi
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引用次数: 29

Abstract

We present a method for removing specular highlight reflections in facial images that may contain varying illumination colors. This is accurately achieved through the use of physical and statistical properties of human skin and faces. We employ a melanin and hemoglobin based model to represent the diffuse color variations in facial skin, and utilize this model to constrain the highlight removal solution in a manner that is effective even for partially saturated pixels. The removal of highlights is further facilitated through estimation of directionally variant illumination colors over the face, which is done while taking advantage of a statistically-based approximation of facial geometry. An important practical feature of the proposed method is that the skin color model is utilized in a way that does not require color calibration of the camera. Moreover, this approach does not require assumptions commonly needed in previous highlight removal techniques, such as uniform illumination color or piecewise-constant surface colors. We validate this technique through comparisons to existing methods for removing specular highlights.
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镜面高光去除在面部图像
我们提出了一种去除面部图像中可能包含不同照明颜色的高光反射的方法。这是通过使用人体皮肤和面部的物理和统计特性准确实现的。我们采用基于黑色素和血红蛋白的模型来表示面部皮肤的漫射颜色变化,并利用该模型以一种即使对部分饱和像素也有效的方式约束高光去除解决方案。通过估计面部方向上不同的照明颜色,进一步促进了高光的去除,这是在利用基于统计的面部几何近似的同时完成的。提出的方法的一个重要的实用特征是肤色模型的利用方式不需要相机的颜色校准。此外,这种方法不需要在以前的高光去除技术中通常需要的假设,例如均匀的照明颜色或分段恒定的表面颜色。我们通过与现有的去除镜面高光的方法进行比较来验证这种技术。
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