Characterization of Human Faces under Illumination Variations Using Rank, Integrability, and Symmetry Constraints
Characterization of Human Faces under Illumination Variations Using Rank, Integrability, and Symmetry Constraints
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DOI：
10.1007/978-3-540-24670-1_45
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发表时间：
2004-05
期刊：
影响因子：
--
通讯作者：
S. Zhou;R. Chellappa;D. Jacobs
中科院分区：
文献类型：
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作者：
S. Zhou;R. Chellappa;D. Jacobs
光度立体算法使用具有不同反照率场的朗伯反射率模型，并且只涉及一个物体的外观。本文将光度立体算法扩展到处理一类中所有物体的所有外观，特别是人脸类。所有面部特征之间的相似性激发了班级反照率和表面法线的等级约束。这导致了由不同光照下不同物体的范例图像组成的观测矩阵的因式分解，这超出了使用双线性分析可以分析的范围。双线性分析需要相同光照下不同物体的样例图像。为了完全恢复类特异性反照率和表面法线，采用了可积性和面对称约束。提出的线性算法通过仅使用表面法线逼近可积项，考虑了反照率场变化的影响。作为一种应用，提出了光照变化下的人脸识别方法。秩约束使算法能够将照明源与观察到的外观分离，并保留适合识别的照明不变信息。使用PIE数据集取得了较好的识别效果。
Photometric stereo algorithms use a Lambertian reflectance model with a varying albedo field and involve the appearances of only one object. This paper extends photometric stereo algorithms to handle all the appearances of all the objects in a class, in particular the class of human faces. Similarity among all facial appearances motivates a rank constraint on the albedos and surface normals in the class. This leads to a factorization of an observation matrix that consists of exemplar images of different objects under different illuminations, which is beyond what can be analyzed using bilinear analysis. Bilinear analysis requires exemplar images of different objects under same illuminations. To fully recover theclass-specificalbedos and surface normals, integrability and face symmetry constraints are employed. The proposed linear algorithm takes into account the effects of the varying albedo field by approximating the integrability terms using only the surface normals. As an application, face recognition under illumination variation is presented. The rank constraint enables an algorithm to separate the illumination source from the observed appearance and keep the illuminant-invariant information that is appropriate for recognition. Good recognition results have been obtained using the PIE dataset.