Illumination cones for recognition under variable lighting: Faces

被引：101

作者：

Georghiades, AS ^{[1
]}

Kriegman, DJ ^{[1
]}

Belhumeur, PN ^{[1
]}

机构：

[1] Yale Univ, Ctr Computat Vis & Control, New Haven, CT 06520 USA

来源：

1998 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS | 1998年

关键词：

D O I：

10.1109/CVPR.1998.698587

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Due to illumination variability, the same object can appear dramatically different even when viewed in fixed pose. To handle this variability, an object recognition system must employ a representation that is either invariant to, or models this variability. Tills paper presents an appearance-based method for modeling the variability due Co illumination in the images of objects. The method differs from past appearance-based methods, however, in that a small set of training images is used to generate a representation - the illumination cone - which models the complete set of images of an object with Lambertian reflectance map under an arbitrary combination of point light sources at infinity. Tilts method is both an implementation and extension (an extension in Mat it models east shadows) of the illumination cone representation proposed in [3]. The method is tested on a database of 660 images of 10 faces, and the results exceed those of popular existing methods.

引用

页码：52 / 58

页数：7