基于稀疏数据表示思想的随机点人脸搜索方法研究

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) Pub Date : 2021-04-28 DOI:10.1109/SIST50301.2021.9465986

K. Maulenov, S. Kudubayeva, A.A. Uvaliyeva

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引用次数: 0

摘要

本文讨论了一种从数字图像中提取特征的方法，该方法基于数据的稀疏表示思想，通过在带有人脸的图像上生成随机点来提取特征。本文说明了该方法与随机蒙特卡罗算法的联系。本文给出了通过系统参数的选择来提高识别精度的实验结果。本文的研究成果可用于以亮度值、像素值为特征的真实识别系统的开发。

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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Studying a Face Search Method Based On the Idea of Sparse Data Representation by Generating Random Points

The article discusses a method for extracting features from digital images, based on the idea of a sparse representation of data by generating random points on images with a face.The article shows the connection of this method with the stochastic Monte Carlo algorithm. Experiments results on the selection of system parameters to increase recognition accuracy are reflected in the article.The conducted research can be used in the development of real recognition systems based on brightness values pixel values as features.

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来源期刊

2021 IEEE International Conference on Smart Information Systems and Technologies (SIST)

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