Age classification from facial images
Age classification from facial images
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DOI：
10.1006/cviu.1997.0549
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发表时间：
1999-04-01
影响因子：
4.5
通讯作者：
Lobo, ND
中科院分区：
文献类型：
--
作者：
Kwon, YH;Lobo, ND
本文提出了一种从人脸图像中进行视觉年龄分类的理论和实际计算方法。目前，该理论仅用于将输入图像分类为三个年龄组之一：婴儿、年轻人和老年人。计算是基于颅面发育理论和皮肤皱纹分析。在实现中，首先找到人脸的主要特征，然后进行次要特征分析。主要特征是眼睛、鼻子、嘴、下巴、头顶和脸的两侧。根据这些特征，计算出区分婴儿与年轻人和老年人的比率。在二次特征分析中，使用皱纹地理图来指导皱纹的检测和测量。计算出的皱纹指数足以将老年人与年轻人和婴儿区分开来。因此，比率和皱纹指数的组合规则允许将面部分类为三个类别之一。使用真实的图像的结果。这是第一个涉及年龄分类的作品，也是第一个成功提取和使用自然皱纹的作品。这也是一个成功的证明，面部特征是足够的分类任务，这一发现是很重要的辩论是什么是适当的面部分析表示。(C)北京：科学出版社.
This paper presents a theory and practical computations for visual age classification from facial images. Currently, the theory has only been implemented to classify input images into one of three age-groups: babies, young adults, and senior adults. The computations are based on cranio-facial development theory and skin wrinkle analysis. In the implementation, primary features of the face are found first, followed by secondary feature analysis. The primary features are the eyes, nose, mouth, chin, virtual-top of the head and the sides of the face. From these features, ratios that distinguish babies from young adults and seniors are computed. In secondary feature analysis, a wrinkle geography map is used to guide the detection and measurement of wrinkles. The wrinkle index computed is sufficient to distinguish seniors from young adults and babies. A combination rule for the ratios and the wrinkle index thus permits categorization of a face into one of three classes. Results using real images are presented. This is the first work involving age classification, and the first work that successfully extracts and uses natural wrinkles. It is also a successful demonstration that facial features are sufficient for a classification task, a finding that is important to the debate about what are appropriate representations for facial analysis. (C) 1999 Academic Press.