一种基于关联的移动设备访问控制人脸验证方案:从算法到Java ME实现

K. Xi, Yan Tang, Jiankun Hu, F. Han
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引用次数: 5

摘要

在本文中,我们研究了专门为配备摄像头的移动设备设计的基于人脸识别的访问控制方法。我们开发了一种基于层次关联的人脸验证(HCFV)方案,该方案可部署于资源最受限的移动设备,如可用内存小于1MB的低端移动电话。HCFV的新颖之处在于执行偏相关输出峰分析(分析从人脸的选定子区域产生的多个互相关峰之间的关系)。在公共领域数据库耶鲁人脸数据库上的实验结果表明,该方法在全尺寸或缩小图像上都比直接使用传统的基于相关的方法取得了更好的性能。此外,为了研究HCFV的适用性和可实现性问题,我们还利用Java ME编程技术在诺基亚S60 CLDC模拟器上实现了HCFV。实验表明,HFVC与传统相关方法相比,占用的内存约为1/10,存储空间约为1/6,处理时间约为3.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A correlation based face verification scheme designed for mobile device access control: From algorithm to Java ME implementation
In this paper, we investigate face recognition based access control approaches dedicatedly designed for camera-equipped mobile devices. We developed a Hierarchical Correlation based Face Verification (HCFV) scheme which is deployable for the most resource constrained mobile devices such as low-end mobile phones with available memory size less than 1MB. The novelty of HCFV is to perform the Partial Correlation Output Peak Analysis (analyze the relations among multiple cross-correlation peaks which are generated from selected sub-regions of a face). The experimental results on the public domain database Yale Face Database demonstrate that the proposed scheme has achieved better performance than using conventional correlation based schemes directly on either full-size or downsized images. Furthermore, in order to investigate the applicability and implementability issues, we have also implemented HCFV on the Nokia S60 CLDC emulator using Java ME programming technology. The experiment shows that HFVC consumes approximately 1/10 memory, 1/6 storage space, and 3.5% processing time in comparison with the result using the conventional correlation methods.
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