The detection of under-eye bags on the facial image

Xiao Jiang, Yong Chai, Wei Xiong, Yi Zhao
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Abstract

In this paper, we propose a novel approach to detect the under-eye bags on the human facial image. The existence and exacerbation of the under-eye bags is one of the significant marks of the facial aging. Once the under-eye bags appear, it not only plays an important impact on the human looks but also gives the impression of the emaciation and senescence. Our experiments and algorithms are based on the image gallery built on our own. The image gallery consists of 8132 facial images of 230 different males which are from different age. The decision of the presence of the under-eye bags in the image is made with the help of the experienced oculists. In the analysis of the facial images, we find several significant features of the under-eye bags in the captured images and design some effective methods to detect them. Base on the our reasonable detection methods, we have designed the under-eye bags classifier. Then we use the whole gallery to evaluate the performance of the classifier. The experiments show that the under-eye bags in the facial image can be well detected with a relatively high accuracy although both the forms of the under-eye bags and the illumination of the image acquisition condition are various.
面部图像上眼袋的检测
本文提出了一种新的人脸图像下眼袋检测方法。眼袋的存在和恶化是面部衰老的显著标志之一。眼袋一旦出现,不仅对人的容貌有重要的影响,而且给人消瘦、衰老的印象。我们的实验和算法是基于我们自己建立的图片库。该图片库由230名不同年龄男性的8132张面部图像组成。在有经验的眼科医生的帮助下,决定图像中是否存在眼袋。在对面部图像的分析中,我们发现了所捕获图像中眼袋的几个显著特征,并设计了一些有效的检测方法。基于我们合理的检测方法,我们设计了眼袋分类器。然后我们使用整个图库来评估分类器的性能。实验表明,尽管面部图像中眼袋的形式和图像采集条件的光照不同,但仍能很好地检测出眼袋,且准确率较高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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