Quick search algorithms based on ethnic facial image database

BaoWei Hou, Rui Zheng, Guosheng Yang
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引用次数: 4

Abstract

The current popular image features index structure can be divided into tree-based structures, hash-based structures and machine learning based structures. In face recognition, selecting the appropriate image feature indexing structure to achieve large-scale face image matching has aways been a problem. In this paper, we present a global image features indexing method based on complete binary tree, using the ethnic facial image database, by contrast with the local sensitive hash(LSH), and principal component analysis (PCA) is adopted to extract facial image features for convienent. Experimental results show that the proposed method is superior to the local sensitive hashing in velocity.
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基于民族人脸图像数据库的快速搜索算法
目前流行的图像特征索引结构可以分为基于树的结构、基于哈希的结构和基于机器学习的结构。在人脸识别中,选择合适的图像特征索引结构来实现大规模的人脸图像匹配一直是一个难题。本文提出了一种基于完全二叉树的全局图像特征索引方法,以民族人脸图像数据库为基础,对比局部敏感哈希(LSH)方法,采用主成分分析(PCA)方法提取人脸图像特征,便于检索。实验结果表明,该方法在速度上优于局部敏感哈希算法。
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