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首页> 外文会议>2014 International Conference on Science Engineering and Management Research >A robust face recognition using automatically detected facial attributes
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A robust face recognition using automatically detected facial attributes

机译：使用自动检测的面部属性进行鲁棒的面部识别

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Immense amount of face image presence led to the dire need for an efficient face recognition approach that can automatically retrieve the preferred face image from the database. Thereby, this paper introduces the use of attributes for efficient face image search. The appearance of images can be described by labelling them with these attributes. This paper mainly focuses on face images and the attributes associated with them. Age, Race, Hair Color, Smiling, Bushy Eyebrows etc., are some of the face attributes. The benefit of using attribute-based face representation is that the face images can be categorized into multiple levels based on the attribute descriptions. For example, one can describe "brown female" for a group of people or "brown female long hair black eyes" for a specific person. We demonstrate the effectiveness of the proposed method by measuring the attribute scores for face images present in PubFig image database. Further, this paper presents a novel and efficient face image representation based on Local Octal Pattern (LOP) texture features. The standard methods (LBP, LTP, LTrP) are able to encode with a maximum of four distinct values about the relationship between the referenced pixel and its corresponding neighbors. The proposed method encodes eight distinct values by calculating the horizontal, vertical and diagonal directions of the pixels using first-order derivatives. The performance of the proposed method is analyzed with the standard methods in terms of average precision and average recall results obtained on PubFig image database.
机译：大量存在的面部图像导致迫切需要一种有效的面部识别方法，该方法可以从数据库中自动检索首选的面部图像。因此，本文介绍了如何使用属性进行有效的人脸图像搜索。可以通过使用这些属性标记图像来描述图像的外观。本文主要关注面部图像及其相关属性。年龄，种族，头发颜色，微笑，浓密的眉毛等都是面部特征。使用基于属性的面部表示的好处是，可以基于属性描述将面部图像分类为多个级别。例如，可以为一群人描述“棕色女性”，或者为特定人描述“棕色女性长发黑眼睛”。我们通过测量PubFig图像数据库中存在的面部图像的属性得分来证明该方法的有效性。此外，本文提出了一种基于局部八进制图案（LOP）纹理特征的新颖且高效的人脸图像表示。标准方法（LBP，LTP，LTrP）最多可以编码四个有关参考像素与其对应邻居之间关系的不同值。所提出的方法通过使用一阶导数计算像素的水平，垂直和对角线方向来编码八个不同的值。在PubFig图像数据库上获得的平均精度和平均召回结果方面，使用标准方法分析了该方法的性能。

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