论文标题
局部四核模式：面部图像识别和检索的新颖描述符
Local Quadruple Pattern: A Novel Descriptor for Facial Image Recognition and Retrieval
论文作者
论文摘要
在本文中，提出了一种新颖的手工制作的本地四倍图案（LQPAT），以用于面部图像识别和检索。大多数现有的手工描述符在当地社区中仅编码有限数量的像素。在不受约束的环境下，这些描述符的性能往往会大大降解。增加当地社区的主要问题是，它还增加了描述符的特征长度。提出的描述符试图通过定义具有最佳特征长度的有效编码结构来克服这些问题。所提出的描述符编码四倍空间中邻居之间的关系。从本地关系计算出两个微模式以形成描述符。将所提出的描述符的检索和识别精度与基准标记数据库中最先进的手工制作的描述符进行了比较。 Caltech-Face，LFW，Colour-fefet和Casia-Face-V5。结果分析表明，所提出的描述符在姿势，照明，背景和表达式的不受控制的变化下表现良好。
In this paper a novel hand crafted local quadruple pattern (LQPAT) is proposed for facial image recognition and retrieval. Most of the existing hand-crafted descriptors encodes only a limited number of pixels in the local neighbourhood. Under unconstrained environment the performance of these descriptors tends to degrade drastically. The major problem in increasing the local neighbourhood is that, it also increases the feature length of the descriptor. The proposed descriptor try to overcome these problems by defining an efficient encoding structure with optimal feature length. The proposed descriptor encodes relations amongst the neighbours in quadruple space. Two micro patterns are computed from the local relationships to form the descriptor. The retrieval and recognition accuracies of the proposed descriptor has been compared with state of the art hand crafted descriptors on bench mark databases namely; Caltech-face, LFW, Colour-FERET, and CASIA-face-v5. Result analysis shows that the proposed descriptor performs well under uncontrolled variations in pose, illumination, background and expressions.
