Benchmark on Face Image Retrieval From Learning Attributes

Tomohiro Hibino, Haoran Xie, K. Miyata
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Abstract

Choosing the most desirable image from many images can be a hard task for a user. In this study, we developed an image selection system based on 4 ways of calculating similarity. We conducted an experiment to validate the usability of the system and decide the best method for recommendation. It was confirmed that our system significantly helps users and Principal Component Analysis is a good way to calculate characteristics from many images.
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基于学习属性的人脸图像检索基准
对于用户来说,从众多图像中选择最理想的图像可能是一项艰巨的任务。在本研究中,我们开发了一个基于4种相似度计算方法的图像选择系统。我们进行了一个实验来验证系统的可用性,并确定最佳的推荐方法。实验证明,我们的系统对用户有很大的帮助,主成分分析是一种很好的方法,可以从许多图像中计算特征。
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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