Hamouz M, Kittler J, Kamarainen J K, Paalanen P, Kälviäinen H, Matas J
Center for Vision, Speech, and Signal Processing, School of Electronics and Physical Sciences, University of Surrey, Guildford, UK.
IEEE Trans Pattern Anal Mach Intell. 2005 Sep;27(9):1490-5. doi: 10.1109/TPAMI.2005.179.
We present a novel method for localizing faces in person identification scenarios. Such scenarios involve high resolution images of frontal faces. The proposed algorithm does not require color, copes well in cluttered backgrounds, and accurately localizes faces including eye centers. An extensive analysis and a performance evaluation on the XM2VTS database and on the realistic BioID and BANCA face databases is presented. We show that the algorithm has precision superior to reference methods.
我们提出了一种在人脸识别场景中定位人脸的新方法。此类场景涉及正面人脸的高分辨率图像。所提出的算法不需要颜色信息,在杂乱背景下表现良好,并且能够准确地定位包括眼睛中心在内的人脸。我们对XM2VTS数据库以及真实的BioID和BANCA人脸数据库进行了广泛的分析和性能评估。我们表明,该算法的精度优于参考方法。