计算机与现代化
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摘要： 传统算法在人脸图像的匹配过程中，需要对每张特征人脸逐个对比，随着图像数量不断增多，对比时间延长，从而降低匹配效率。提出一种基于云的海量人脸特征匹配算法，首先通过广域云网络模型来提取人脸特征权值参数，然后对特征参数矩阵转换处理，最后应用转化后的矩阵匹配人脸特征。应用该方法构建的云平台，结合改进的ASM算法预判模型特征，可以更有效提高匹配程度。实验表明，本文算法在对海量人脸图像匹配中，具有较传统算法耗时更少的优点。
关键词: 云计算, 人脸, 特征匹配
Abstract: In the process of matching facial images, the traditional algorithm compares each face’s features one by one. With the increase of images, the comparison time prolongs which leads to the low match efficiency. A match algorithm of mass facial feature based on cloud is proposed. First, the weighting parameters of facial features are extracted by inter-cloud network models. Then, the transformation processing of the features’ parameter matrix is conducted. Last, this matrix is applied to matching facial features. The cloud platform based on this method combines the features of the improved ASM algorithm’s early-detection model which helps match. Experimental result shows that the suggested algorithm has the advantage of less time-consuming compared with the traditional one in the match of mass facial images.
Key words: cloud computing, face, feature match
中图分类号:
TP391
张志强 . 基于云计算的大规模人脸特征检索[J]. 计算机与现代化, doi: 10.3969/j.issn.1006-2475.2014.07.016.
ZHANG Zhi-qiang. Large-scale Facial Feature Retrieval Based on Cloud Computing[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2014.07.016.
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链接本文: http://www.c-a-m.org.cn/CN/10.3969/j.issn.1006-2475.2014.07.016
http://www.c-a-m.org.cn/CN/Y2014/V0/I7/71
