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Performance Evaluation and Comparison of Software for Face Recognition, Based on Dlib and Opencv Library

机译:基于DLIB和OpenCV库的人脸识别软件的性能评估与比较

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Overview and investigate time complexity of computer vision algorithms for face recognition. Main article idea is to compare two popular computer vision librarieobjs, they are OpenCV and dlib, explore features, analyze pros and cons each of them and understand in what situation each of them suit the best. Method. The technologies of computer vision, which are used for face recognition was worked out. Research of two popular computer vision libraries was conducted. Their features are analyzed and the advantages and disadvantages of each of them are estimated. Examples of building recognition application based on histogram-oriented gradients for face finding, face landmark estimation for face orientation, and deep convolutional neural network to compare with known faces. The article generalizes the concept of face recognition. The scientific basis for facial recognition and the construction of a complete recognition system was described. The basic principles of the programs for face recognition are formulated. A comparative analysis of the productivity of both libraries in relation to - the time of execution to the number of iterations of the applied algorithms was presented. Also built two simple applications for face recognition based on these libraries and comparing their performance.
机译:概述和调查计算机视觉算法对人脸识别的时间复杂性。主要文章的想法是比较两个流行的计算机Vision LibraInieobs,它们是OpenCV和DLIB,探索特征,分析优点,并涉及它们中的每一个,并理解他们每个人都适合最佳状态。方法。用于人脸识别的计算机视觉技术进行了效果。进行了两个流行的计算机视觉图书馆的研究。分析了它们的特征,估计它们中的每一个的优点和缺点。基于针对面向面积的直方图取向梯度的构建识别应用的示例,面向面向面向面部定向的地形估计,以及与已知面部比较的深度卷积神经网络。文章概括了人脸识别的概念。描述了面部识别的科学依据和完整识别系统的构建。制定了面部识别计划的基本原则。介绍了与 - 应用算法迭代次数的关系中两个文库的生产率的比较分析。还基于这些库建立了两个简单的面部识别应用程序,并比较了它们的性能。

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