鲁棒人脸识别的平均分段部分Hausdorff距离

Hamidreza Dastmalchi, Javad Jafaryahya, Reza Najafi, A. Daneshkhah
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引用次数: 2

摘要

人脸识别是一种非接触的生物识别技术,它试图根据个人的图像自动验证个人。计算时间和准确率是人脸识别系统需要考虑的重要方面。华氏距离是一种测量两个点集之间不相似度的方法,已越来越多地用于人脸识别。在本文中,我们提出了一种基于Hausdorff距离的改进准则,显著减少了传统人脸识别方法中基于Hausdorff距离的过多计算时间,同时提高了识别率。
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Averaged Segmental Partial Hausdorff Distance for Robust Face Recognition
Face recognition is a non-contact biometric identification that tries to verify individuals automatically based on their images. Computational time and accuracy rate are important aspects to be considered for Face Recognition systems. Huasdorff distance is a dissimilarity measurement between two point sets which has been increasingly used for face recognition. In this paper, we have proposed a modified criterion based on Hausdorff distance, which conspicuously decreases the excessive computational time while increases the recognition rate of conventional face recognition methods, based on Hausdorff distance.
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