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Novel local feature extraction for age invariant face recognition
Expert Systems with Applications ( IF 7.5 ) Pub Date : 2021-03-04 , DOI: 10.1016/j.eswa.2021.114786
Rajesh Kumar Tripathi , Anand Singh Jalal

Age variation is a major problem in the area of face recognition under uncontrolled environments such as pose variation, lighting effects, expression etc. Most of the works of this area have used discriminative feature descriptors. These discriminative feature descriptors are based on their fixed encoding which considers pixels of different radial widths for feature extraction and ignores some radii pixels which hold important discriminative information for age variation. Therefore, consideration of all the pixels of the local region is necessary for important feature extraction in the case of age invariant face recognition. This paper introduces a novel local feature descriptor to find difference pattern and dual directional relation pattern for age invariant face recognition. The proposed descriptor is applied over the preprocessed face images and its parts-periocular region i.e. left and right eye, mouth and nose region of a face image. The proposed difference pattern and dual directional relation pattern descriptors extract the texture features on the local region of a specified dimension. Chi-square metric has been used for finding the similarity between probe and gallery images. Evaluation of the proposed feature descriptor has been performed on two standard challenging datasets FGNET and MORPH for age invariant face recognition. The proposed descriptor performed well and outperformed to the existing age invariant face recognition state-of-the-art methods on FGNET dataset and also performed well on MORPH dataset.



中文翻译:

新颖的局部特征提取技术用于年龄不变的人脸识别

年龄变化是在不受控制的环境(例如姿势变化,光照效果,表情等)下的人脸识别领域中的一个主要问题。该领域的大多数工作都使用了区分性特征描述符。这些区分特征描述符基于它们的固定编码,该固定编码考虑了不同径向宽度的像素以进行特征提取,并忽略了一些半径像素,这些半径像素保留了重要的区分信息以用于年龄变化。因此,在年龄不变的面部识别的情况下,对于重要的特征提取,必须考虑局部区域的所有像素。本文介绍了一种新颖的局部特征描述符,用于寻找年龄不变的人脸识别的差异模式和双向关系模式。所提出的描述符被应用到预处理的面部图像及其部分眼周区域,即面部图像的左眼和右眼,嘴巴和鼻子区域。所提出的差异图案和双向关系图案描述符提取指定尺寸的局部区域上的纹理特征。卡方度量已用于查找探针图像和图库图像之间的相似性。已针对年龄不变的人脸识别在两个标准的具有挑战性的数据集FGNET和MORPH上对提出的特征描述符进行了评估。所提出的描述符在FGNET数据集上表现良好,并且优于现有的年龄不变脸部识别最新技术,在MORPH数据集上也表现良好。所提出的差异图案和双向关系图案描述符提取指定尺寸的局部区域上的纹理特征。卡方度量已用于查找探针图像和图库图像之间的相似性。已针对年龄不变的人脸识别在两个标准的具有挑战性的数据集FGNET和MORPH上对提出的特征描述符进行了评估。所提出的描述符在FGNET数据集上表现良好,并且优于现有的年龄不变脸部识别最新技术,在MORPH数据集上也表现良好。所提出的差异图案和双向关系图案描述符提取指定尺寸的局部区域上的纹理特征。卡方度量已用于查找探针图像和图库图像之间的相似性。对两个标准的具有挑战性的数据集FGNET和MORPH进行了评估,用于年龄不变的人脸识别。所提出的描述符在FGNET数据集上表现良好,并且优于现有的年龄不变的人脸识别最新技术方法,在MORPH数据集上也表现良好。已针对年龄不变的人脸识别在两个标准的具有挑战性的数据集FGNET和MORPH上对提出的特征描述符进行了评估。所提出的描述符在FGNET数据集上表现良好,并且优于现有的年龄不变脸部识别最新技术,在MORPH数据集上也表现良好。已针对年龄不变的人脸识别在两个标准的具有挑战性的数据集FGNET和MORPH上对提出的特征描述符进行了评估。所提出的描述符在FGNET数据集上表现良好,并且优于现有的年龄不变脸部识别最新技术,在MORPH数据集上也表现良好。

更新日期:2021-03-17
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