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基于物理的化妆品模拟:通过带面部先验的本征图像分解实现

Physically-Based Simulation of Cosmetics via Intrinsic Image Decomposition with Facial Priors.

作者信息

Lin Stephen

出版信息

IEEE Trans Pattern Anal Mach Intell. 2019 Jun;41(6):1455-1469. doi: 10.1109/TPAMI.2018.2832059. Epub 2018 May 1.

Abstract

We present a physically-based approach for simulating makeup in face images. The key idea is to decompose the face image into intrinsic image layers - namely albedo, diffuse shading, and specular highlights - which are each differently affected by cosmetics, and then manipulate each layer according to corresponding models of reflectance. Accurate intrinsic image decompositions for faces are obtained with the help of human face priors, including statistics on skin reflectance and facial geometry. The intrinsic image layers are then transformed in appearance according to measured optical properties of cosmetics and proposed adaptations of physically-based reflectance models. With this approach, realistic results are generated in a manner that preserves the personal appearance features and lighting conditions of the target face while not requiring detailed geometric and reflectance measurements. We demonstrate this technique on various forms of cosmetics including foundation, blush, lipstick, and eye shadow. Results on both images and videos exhibit a close approximation to ground truth and compare favorably to existing techniques.

摘要

我们提出了一种基于物理的方法来模拟面部图像中的妆容。关键思想是将面部图像分解为固有图像层,即反照率、漫反射阴影和镜面高光,它们受化妆品的影响各不相同,然后根据相应的反射模型对每层进行处理。借助人脸先验知识,包括皮肤反射率和面部几何形状的统计信息,可获得准确的面部固有图像分解。然后,根据测量的化妆品光学特性和提出的基于物理的反射模型改编,对固有图像层的外观进行变换。通过这种方法,生成的逼真结果既能保留目标面部的个人外观特征和光照条件,又无需详细的几何和反射率测量。我们在包括粉底、腮红、口红和眼影在内的各种化妆品上演示了这项技术。图像和视频的结果都与真实情况非常接近,并且与现有技术相比具有优势。

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