Local Color Vector Binary Patterns From Multichannel Face Images for Face Recognition
Local Color Vector Binary Patterns From Multichannel Face Images for Face Recognition
复制标题
DOI：
10.1109/tip.2011.2181526
复制
发表时间：
2012-04-01
影响因子：
10.6
通讯作者：
Plataniotis, Konstantinos N.
中科院分区：
文献类型：
--
作者：
Lee, Seung Ho;Choi, Jae Young;Plataniotis, Konstantinos N.
提出了一种基于颜色信息的人脸描述子，所谓的局部颜色向量二进制模式（LCVBP），用于人脸识别（FR）。LCVBP由两个判别模式组成：颜色范数模式和颜色角度模式。特别是，我们设计了一种方法提取颜色的角度图案，这使得编码的区别纹理图案来自不同的光谱波段图像之间的空间相互作用。为了执行FR任务，建议的LCVBP特征是通过组合从颜色范数模式和颜色角度模式中提取的多个特征来生成的。已经进行了广泛的和比较实验，以评估拟议的LCVBP功能在五个公共数据库。实验结果表明，所提出的LCVBP特征能够产生良好的FR性能的挑战性的人脸图像。此外，建议的LCVBP功能的有效性已成功地通过比较其他国家的最先进的人脸描述符进行了测试。
This paper proposes a novel face descriptor based on color information, i.e., so-called local color vector binary patterns (LCVBPs), for face recognition (FR). The proposed LCVBP consists of two discriminative patterns: color norm patterns and color angular patterns. In particular, we have designed a method for extracting color angular patterns, which enables to encode the discriminating texture patterns derived from spatial interactions among different spectral-band images. In order to perform FR tasks, the proposed LCVBP feature is generated by combining multiple features extracted from both color norm patterns and color angular patterns. Extensive and comparative experiments have been conducted to evaluate the proposed LCVBP feature on five public databases. Experimental results show that the proposed LCVBP feature is able to yield excellent FR performance for challenging face images. In addition, the effectiveness of the proposed LCVBP feature has successfully been tested by comparing other state-of-the-art face descriptors.