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Alternative TitleFace Image Analysis under Variable Illumination
Thesis Advisor卢汉清 ; 沈向洋
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword人脸去光照 多光照下的人脸重建 人脸对准 二阶对准 Face De-lighting Face Relighting Under Varying Illumination Face Alignment Bi-stage Alignment
Abstract人脸的外观是由光和人脸表面的相互作用决定的,光照条件和人脸表面反 射属性的变化会引起人脸外观的显著变化;这给与人脸分析相关的计算视觉应 用带来了很大的挑战。因此长期以来,可变光照下的人脸分析都是计算机视觉 领域的重要课题。本文首先对与此相关的的工作做了回顾,然后重点讨论了这 一问题的两个子问题: (一)人脸去光照和多光照下的人脸图像重建, (二) 可变光照下的人脸对准。 从单幅图像中恢复对光照条件具有不变性的反射率图像是非常困难的,因 为在数学上这是一个病态问题。基于形状相似性的假设,本文的第一个工作 提出了一种存在于反射率图像及其相关的不同光照下图像之间的结构上的相似 性;然后利用这种结构相似性设计了一种简单的线性重建的方法从图像训练集 合中恢复反射率图像。在重建的过程中使用了主元分析方法来得到鲁棒的重建 结果。实验表明,这种方法能够有效地从单幅图像中去除光照变化对人脸图像 分析的影响;而且,它可以直接被应用于多光照下的人脸图像重建。 本文的第二个工作讨论了在以前的二维对准工作中被忽略的一个障碍性问 题:可变光照下的人脸对准。第四章首先介绍了什么是人脸对准,现有的人脸 对准方法为什么对光照变化不鲁棒;然后讨论怎么平抑光照变化带来的影响。 本文使用了两种对光照具有相对不变性的信息用于人脸对准:相位一致性边缘 和本质灰度信息。显著的边缘特征在明暗及其阴影效果明显的的情况下也能够 被有效地定位,因此可以将相位一致性边缘用于人脸的粗略对准阶段;为了精 确定位那些不太显著的边缘,一种局部均衡化的方法被提出以求得本质灰度信 息,并用于人脸的精细对准阶段。大量实验证明,这一人脸对准系统能够准确 有效地对准很大范围光照下的人脸图像。 最后,本文对上述工作可能的扩展和在别的相关研究中的应用做了展望。
Other AbstractThe appearance of human face is determined by the interaction between light and matter on the face. Changes in illumination conditions or surface reflectance properties of human face can lead to significant variations in the appearance of face. Therefore For a long time face image analysis under variable i11umination is an important task to computer vision society. At first this thesis gives a brief retrospect to the related work. Then we focus on the following two subproblems: face de-lighting & relighting, and face alignment under variable illumination. It is very difficult to recover the illumination-invariant reflectance from a single input image because it is an ill conditioned problem. In our first work structure similarity between the reflectance image and its illuminated image is revealed firstly based on an ideal class definition. Then a simple linear reconstruction scheme is successfully proposed for reflectance rendering, in which the reflectance face images are learnt (or generated) from the training examples in terms of this structure similarity. Principal Component Analysis is adopted to get a robust rendering result. Extensive experiments show that the proposed method is efficacious in separating reflectance from an input face image, and reducing the variation caused by lighting conditions. Furthermore, this method can be used directly to render new images of the input face under different lighting conditions. Our second work presents an approach to face alignment under variable illumination, an obstacle largely ignored in previous 2D alignment work. Firstly we introduce what is face alignment and why the traditional methods to face alignment can not handle illumination variation. Then we discuss how to employ two forms of relatively lighting-invariant information to account for illumination variation. Edge phase congruency is adopted to coarsely localize facial features, since prominent feature edges can be robustly located in the presence of shading and shadows. To accurately deal with features with less pronounced edges, final alignment is then computed from intrinsic gray-level information recovered using a proposed form of local intensity normalization. With this approach, our face alignment system works efficiently and effectively under a wide range of illumination conditions, as evidenced by extensive experimentation. At last we discuss some possible extensions of our research work and point out their perspective applications.
Other Identifier794
Document Type学位论文
Recommended Citation
GB/T 7714
黄郁驰. 可变光照下的人脸图像分析[D]. 中国科学院自动化研究所. 中国科学院研究生院,2004.
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