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The PCA-Based Long Distance Face Recognition Using Multiple Distance Training Images for Intelligent Surveillance System

机译:基于PCA的长距离面部识别,使用多距离训练图像进行智能监控系统

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摘要

In this paper, PCA-based long distance face recognition algorithm applicable to the environment of intelligent video surveillance system is proposed. While the existing face recognition algorithm uses the short distance images for training images, the proposed algorithm uses face images by distance extracted from 1m to 5m for training images. Face images by distance, which are used for training images and test images, are normalized through bilinear interpolation. The proposed algorithm has improved face recognition performance by 4.8% in short distance and 16.5% in long distance so it is applicable to the intelligent video surveillance system.
机译:本文提出了适用于智能视频监控系统环境的PCA的长距离面识算法。虽然现有的人脸识别算法使用短距离图像进行训练图像,但是该算法通过从1M到5M提取的距离以进行训练图像的距离。通过用于训练图像和测试图像的距离的面部图像通过双线性插值标准化。所提出的算法在短距离中提高了面部识别性能4.8%,长距离16.5%,因此适用于智能视频监控系统。

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